Facilitating environment-based lossy compression of data for efficient rendering of contents at computing devices

ABSTRACT

A mechanism is described for facilitating environment-based lossy compression of data for efficient rendering of contents at computing devices. A method of embodiments, as described herein, includes collecting, in real time, sensory input data relating to characteristics of at least one of a user and a surrounding environment. The method may further include evaluating the sensory input data to mark one or more data portions of data relating to contents, where the one or more data portions are determined to be suitable for compression based on the sensory input data. The method may further include dynamically performing, in real time, the compression of the one or more data portions, where the compression triggers loss of one or more content portions of the contents corresponding to the one or more data portions of the data. The method may further include rendering the contents to be displayed missing the one or more content portions, where the missing of the one or more content portions from the contents is not apparent to the user viewing the contents via a display device.

FIELD

Embodiments described herein generally relate to computers. Moreparticularly, embodiments relate to a mechanism for facilitatingenvironment-based lossy compression of data for efficient rendering ofcontents at computing devices.

BACKGROUND

Conventional compression techniques are based on predefined data orrough estimates that are based on a defined reference environment andtherefore incapable of obtaining and predicting certain reference pointswhich leads to inefficiencies and inaccuracies.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments are illustrated by way of example, and not by way oflimitation, in the figures of the accompanying drawings in which likereference numerals refer to similar elements.

FIG. 1 is a block diagram of a processing system, according to anembodiment.

FIG. 2 is a block diagram of an embodiment of a processor having one ormore processor cores, an integrated memory controller, and an integratedgraphics processor.

FIG. 3 is a block diagram of a graphics processor, which may be adiscrete graphics processing unit, or may be a graphics processorintegrated with a plurality of processing cores.

FIG. 4 is a block diagram of a graphics processing engine of a graphicsprocessor in accordance with some embodiments.

FIG. 5 is a block diagram of another embodiment of a graphics processor.

FIG. 6 illustrates thread execution logic including an array ofprocessing elements employed in some embodiments of a graphicsprocessing engine.

FIG. 7 is a block diagram illustrating a graphics processor instructionformats according to some embodiments.

FIG. 8 is a block diagram of another embodiment of a graphics processor.

FIG. 9A is a block diagram illustrating a graphics processor commandformat according to an embodiment and FIG. 9B is a block diagramillustrating a graphics processor command sequence according to anembodiment.

FIG. 10 illustrates exemplary graphics software architecture for a dataprocessing system according to some embodiments.

FIG. 11 is a block diagram illustrating an IP core development systemthat may be used to manufacture an integrated circuit to performoperations according to an embodiment.

FIG. 12 is a block diagram illustrating an exemplary system on a chipintegrated circuit that may be fabricated using one or more IP cores,according to an embodiment.

FIG. 13 illustrates a computing device employing a real-time selectivedata compression mechanism according to one embodiment.

FIG. 14 illustrates a real-time selective data compression mechanismaccording to one embodiment.

FIG. 15 illustrates a visual field in consideration for real-time anddynamic lossy compression of data according to one embodiment.

FIG. 16A illustrates a method for collection and use of sensory inputdata at various rendering stages according to one embodiment.

FIG. 16B illustrates a method for tile-based color compression accordingto one embodiment.

FIG. 16C illustrates a method for real-time and dynamic loss compressionof data according to one embodiment.

DETAILED DESCRIPTION

In the following description, numerous specific details are set forth.However, embodiments, as described herein, may be practiced withoutthese specific details. In other instances, well-known circuits,structures and techniques have not been shown in details in order not toobscure the understanding of this description.

Embodiments provide for a novel technique for real-time compression ofdata based on its relevance to a corresponding user (also referred to as“viewer”) of a computing device and a viewing environment associatedwith the user and/or the computing device such that the real-time datamay be interpreted and manipulated by the graphics processor at thecomputing device to facilitate data compression on such a level thatalthough the compression may be lossy, any relevant loss may bevirtually impossible or at least extremely difficult to detect by theuser.

In one embodiment, as will be further described throughout thisdocument, the real-time data may be obtained through real-time inputsignals, such as using one or more input devices (e.g., cameras,sensors, detectors, etc.), where the real-time data may provide thenecessary leveraging knowledge about the user and the viewingenvironment to then be used for adjusting codecs for real-timegeneration of content to, for example, minimize data traffic whilemaximizing perceived image quality.

For example, through numerous researches relating to human behavior,etc., it is contemplated that a user is typically focused on thecore/middle of an image as opposed to the periphery of the image andaccordingly, in one embodiment, using the novel lossy compressiontechnique, a certain amount of data in the periphery of the image may becompressed such that some of the peripheral bits may be removed toprovide for a more efficient rendering of the image. This removal andefficient rendering may be accomplished without having to compromise theimage quality or the user's viewing experience, where the user fails tonotice any of the content loss associated with the removed peripheralbits (because the user is not expected to look as closely in theperipheral parts of the image). In another embodiment, eye tracking(also referred to as “gaze tracking”) may be used to track the user'sgaze, such as where the user is looking, and the compress operation isdone with higher loss, such as in chroma, etc., the farther away fromthe point where the user is looking.

Similarly, in one embodiment, real-time sensory input data (alsoreferred to as “sensory data”) relating to the user and the surroundingenvironment may be monitored and obtained, in real-time, to dynamicallyand continually perform lossy compression for efficient rendering ofdata at various rendering stages without compromising the userexperience. For example, a depth sensing camera may be used to monitorhow far the user is from the display screen and if the distance issufficiently large, a high resolution display of content may not benecessitated and thus, in one embodiment, some of the data may becompressed without the user noticing the loss. However, if the usersuddenly gets closer to the display screen, as sensed by the depthsensing camera, in one embodiment, the compression may be reduced orterminated and the high resolution content display may be restored.

In some embodiments, terms like “display screen” and “display surface”may be used interchangeably referring to the visible portion of adisplay device while the rest of the display device may be embedded intoa computing device, such as a smartphone, a wearable device, etc. It iscontemplated and to be noted that embodiments are not limited to anyparticular computing device, software application, hardware component,display device, display screen or surface, protocol, standard, etc. Forexample, embodiments may be applied to and used with any number and typeof real-time applications on any number and type of computers, such asdesktops, laptops, tablet computers, smartphones, head-mounted displaysand other wearable devices, and/or the like. Further, for example,rendering scenarios using this novel real-time data-based compressiontechnique may range from simple scenarios, such as desktop compositing,to complex scenarios, such as three-dimension (3D) games, augmentedreality applications, etc.

System Overview

FIG. 1 is a block diagram of a processing system 100, according to anembodiment. In various embodiments the system 100 includes one or moreprocessors 102 and one or more graphics processors 108, and may be asingle processor desktop system, a multiprocessor workstation system, ora server system having a large number of processors 102 or processorcores 107. In on embodiment, the system 100 is a processing platformincorporated within a system-on-a-chip (SoC) integrated circuit for usein mobile, handheld, or embedded devices.

An embodiment of system 100 can include, or be incorporated within aserver-based gaming platform, a game console, including a game and mediaconsole, a mobile gaming console, a handheld game console, or an onlinegame console. In some embodiments system 100 is a mobile phone, smartphone, tablet computing device or mobile Internet device. Dataprocessing system 100 can also include, couple with, or be integratedwithin a wearable device, such as a smart watch wearable device, smarteyewear device, augmented reality device, or virtual reality device. Insome embodiments, data processing system 100 is a television or set topbox device having one or more processors 102 and a graphical interfacegenerated by one or more graphics processors 108.

In some embodiments, the one or more processors 102 each include one ormore processor cores 107 to process instructions which, when executed,perform operations for system and user software. In some embodiments,each of the one or more processor cores 107 is configured to process aspecific instruction set 109. In some embodiments, instruction set 109may facilitate Complex Instruction Set Computing (CISC), ReducedInstruction Set Computing (RISC), or computing via a Very LongInstruction Word (VLIW). Multiple processor cores 107 may each process adifferent instruction set 109, which may include instructions tofacilitate the emulation of other instruction sets. Processor core 107may also include other processing devices, such a Digital SignalProcessor (DSP).

In some embodiments, the processor 102 includes cache memory 104.Depending on the architecture, the processor 102 can have a singleinternal cache or multiple levels of internal cache. In someembodiments, the cache memory is shared among various components of theprocessor 102. In some embodiments, the processor 102 also uses anexternal cache (e.g., a Level-3 (L3) cache or Last Level Cache (LLC))(not shown), which may be shared among processor cores 107 using knowncache coherency techniques. A register file 106 is additionally includedin processor 102 which may include different types of registers forstoring different types of data (e.g., integer registers, floating pointregisters, status registers, and an instruction pointer register). Someregisters may be general-purpose registers, while other registers may bespecific to the design of the processor 102.

In some embodiments, processor 102 is coupled to a processor bus 110 totransmit communication signals such as address, data, or control signalsbetween processor 102 and other components in system 100. In oneembodiment the system 100 uses an exemplary ‘hub’ system architecture,including a memory controller hub 116 and an Input Output (I/O)controller hub 130. A memory controller hub 116 facilitatescommunication between a memory device and other components of system100, while an I/O Controller Hub (ICH) 130 provides connections to I/Odevices via a local I/O bus. In one embodiment, the logic of the memorycontroller hub 116 is integrated within the processor.

Memory device 120 can be a dynamic random access memory (DRAM) device, astatic random access memory (SRAM) device, flash memory device,phase-change memory device, or some other memory device having suitableperformance to serve as process memory. In one embodiment the memorydevice 120 can operate as system memory for the system 100, to storedata 122 and instructions 121 for use when the one or more processors102 executes an application or process. Memory controller hub 116 alsocouples with an optional external graphics processor 112, which maycommunicate with the one or more graphics processors 108 in processors102 to perform graphics and media operations.

In some embodiments, ICH 130 enables peripherals to connect to memorydevice 120 and processor 102 via a high-speed I/O bus. The I/Operipherals include, but are not limited to, an audio controller 146, afirmware interface 128, a wireless transceiver 126 (e.g., Wi-Fi,Bluetooth), a data storage device 124 (e.g., hard disk drive, flashmemory, etc.), and a legacy I/O controller 140 for coupling legacy(e.g., Personal System 2 (PS/2)) devices to the system. One or moreUniversal Serial Bus (USB) controllers 142 connect input devices, suchas keyboard and mouse 144 combinations. A network controller 134 mayalso couple to ICH 130. In some embodiments, a high-performance networkcontroller (not shown) couples to processor bus 110. It will beappreciated that the system 100 shown is exemplary and not limiting, asother types of data processing systems that are differently configuredmay also be used. For example, the I/O controller hub 130 may beintegrated within the one or more processor 102, or the memorycontroller hub 116 and I/O controller hub 130 may be integrated into adiscreet external graphics processor, such as the external graphicsprocessor 112.

FIG. 2 is a block diagram of an embodiment of a processor 200 having oneor more processor cores 202A-202N, an integrated memory controller 214,and an integrated graphics processor 208. Those elements of FIG. 2having the same reference numbers (or names) as the elements of anyother figure herein can operate or function in any manner similar tothat described elsewhere herein, but are not limited to such. Processor200 can include additional cores up to and including additional core202N represented by the dashed lined boxes. Each of processor cores202A-202N includes one or more internal cache units 204A-204N. In someembodiments each processor core also has access to one or more sharedcached units 206.

The internal cache units 204A-204N and shared cache units 206 representa cache memory hierarchy within the processor 200. The cache memoryhierarchy may include at least one level of instruction and data cachewithin each processor core and one or more levels of shared mid-levelcache, such as a Level 2 (L2), Level 3 (L3), Level 4 (L4), or otherlevels of cache, where the highest level of cache before external memoryis classified as the LLC. In some embodiments, cache coherency logicmaintains coherency between the various cache units 206 and 204A-204N.

In some embodiments, processor 200 may also include a set of one or morebus controller units 216 and a system agent core 210. The one or morebus controller units 216 manage a set of peripheral buses, such as oneor more Peripheral Component Interconnect buses (e.g., PCI, PCIExpress). System agent core 210 provides management functionality forthe various processor components. In some embodiments, system agent core210 includes one or more integrated memory controllers 214 to manageaccess to various external memory devices (not shown).

In some embodiments, one or more of the processor cores 202A-202Ninclude support for simultaneous multi-threading. In such embodiment,the system agent core 210 includes components for coordinating andoperating cores 202A-202N during multi-threaded processing. System agentcore 210 may additionally include a power control unit (PCU), whichincludes logic and components to regulate the power state of processorcores 202A-202N and graphics processor 208.

In some embodiments, processor 200 additionally includes graphicsprocessor 208 to execute graphics processing operations. In someembodiments, the graphics processor 208 couples with the set of sharedcache units 206, and the system agent core 210, including the one ormore integrated memory controllers 214. In some embodiments, a displaycontroller 211 is coupled with the graphics processor 208 to drivegraphics processor output to one or more coupled displays. In someembodiments, display controller 211 may be a separate module coupledwith the graphics processor via at least one interconnect, or may beintegrated within the graphics processor 208 or system agent core 210.

In some embodiments, a ring based interconnect unit 212 is used tocouple the internal components of the processor 200. However, analternative interconnect unit may be used, such as a point-to-pointinterconnect, a switched interconnect, or other techniques, includingtechniques well known in the art. In some embodiments, graphicsprocessor 208 couples with the ring interconnect 212 via an I/O link213.

The exemplary I/O link 213 represents at least one of multiple varietiesof I/O interconnects, including an on package I/O interconnect whichfacilitates communication between various processor components and ahigh-performance embedded memory module 218, such as an eDRAM module. Insome embodiments, each of the processor cores 202-202N and graphicsprocessor 208 use embedded memory modules 218 as a shared Last LevelCache.

In some embodiments, processor cores 202A-202N are homogenous coresexecuting the same instruction set architecture. In another embodiment,processor cores 202A-202N are heterogeneous in terms of instruction setarchitecture (ISA), where one or more of processor cores 202A-N executea first instruction set, while at least one of the other cores executesa subset of the first instruction set or a different instruction set. Inone embodiment processor cores 202A-202N are heterogeneous in terms ofmicroarchitecture, where one or more cores having a relatively higherpower consumption couple with one or more power cores having a lowerpower consumption. Additionally, processor 200 can be implemented on oneor more chips or as an SoC integrated circuit having the illustratedcomponents, in addition to other components.

FIG. 3 is a block diagram of a graphics processor 300, which may be adiscrete graphics processing unit, or may be a graphics processorintegrated with a plurality of processing cores. In some embodiments,the graphics processor communicates via a memory mapped I/O interface toregisters on the graphics processor and with commands placed into theprocessor memory. In some embodiments, graphics processor 300 includes amemory interface 314 to access memory. Memory interface 314 can be aninterface to local memory, one or more internal caches, one or moreshared external caches, and/or to system memory.

In some embodiments, graphics processor 300 also includes a displaycontroller 302 to drive display output data to a display device 320.Display controller 302 includes hardware for one or more overlay planesfor the display and composition of multiple layers of video or userinterface elements. In some embodiments, graphics processor 300 includesa video codec engine 306 to encode, decode, or transcode media to, from,or between one or more media encoding formats, including, but notlimited to Moving Picture Experts Group (MPEG) formats such as MPEG-2,Advanced Video Coding (AVC) formats such as H.264/MPEG-4 AVC, as well asthe Society of Motion Picture & Television Engineers (SMPTE) 421M/VC-1,and Joint Photographic Experts Group (JPEG) formats such as JPEG, andMotion JPEG (MJPEG) formats.

In some embodiments, graphics processor 300 includes a block imagetransfer (BLIT) engine 304 to perform two-dimensional (2D) rasterizeroperations including, for example, bit-boundary block transfers.However, in one embodiment, 2D graphics operations are performed usingone or more components of graphics processing engine (GPE) 310. In someembodiments, graphics processing engine 310 is a compute engine forperforming graphics operations, including three-dimensional (3D)graphics operations and media operations.

In some embodiments, GPE 310 includes a 3D pipeline 312 for performing3D operations, such as rendering three-dimensional images and scenesusing processing functions that act upon 3D primitive shapes (e.g.,rectangle, triangle, etc.). The 3D pipeline 312 includes programmableand fixed function elements that perform various tasks within theelement and/or spawn execution threads to a 3D/Media sub-system 315.While 3D pipeline 312 can be used to perform media operations, anembodiment of GPE 310 also includes a media pipeline 316 that isspecifically used to perform media operations, such as videopost-processing and image enhancement.

In some embodiments, media pipeline 316 includes fixed function orprogrammable logic units to perform one or more specialized mediaoperations, such as video decode acceleration, video de-interlacing, andvideo encode acceleration in place of, or on behalf of video codecengine 306. In some embodiments, media pipeline 316 additionallyincludes a thread spawning unit to spawn threads for execution on3D/Media sub-system 315. The spawned threads perform computations forthe media operations on one or more graphics execution units included in3D/Media sub-system 315.

In some embodiments, 3D/Media subsystem 315 includes logic for executingthreads spawned by 3D pipeline 312 and media pipeline 316. In oneembodiment, the pipelines send thread execution requests to 3D/Mediasubsystem 315, which includes thread dispatch logic for arbitrating anddispatching the various requests to available thread executionresources. The execution resources include an array of graphicsexecution units to process the 3D and media threads. In someembodiments, 3D/Media subsystem 315 includes one or more internal cachesfor thread instructions and data. In some embodiments, the subsystemalso includes shared memory, including registers and addressable memory,to share data between threads and to store output data.

3D/Media Processing

FIG. 4 is a block diagram of a graphics processing engine 410 of agraphics processor in accordance with some embodiments. In oneembodiment, the GPE 410 is a version of the GPE 310 shown in FIG. 3.Elements of FIG. 4 having the same reference numbers (or names) as theelements of any other figure herein can operate or function in anymanner similar to that described elsewhere herein, but are not limitedto such.

In some embodiments, GPE 410 couples with a command streamer 403, whichprovides a command stream to the GPE 3D and media pipelines 412, 416. Insome embodiments, command streamer 403 is coupled to memory, which canbe system memory, or one or more of internal cache memory and sharedcache memory. In some embodiments, command streamer 403 receivescommands from the memory and sends the commands to 3D pipeline 412and/or media pipeline 416. The commands are directives fetched from aring buffer, which stores commands for the 3D and media pipelines 412,416. In one embodiment, the ring buffer can additionally include batchcommand buffers storing batches of multiple commands. The 3D and mediapipelines 412, 416 process the commands by performing operations vialogic within the respective pipelines or by dispatching one or moreexecution threads to an execution unit array 414. In some embodiments,execution unit array 414 is scalable, such that the array includes avariable number of execution units based on the target power andperformance level of GPE 410.

In some embodiments, a sampling engine 430 couples with memory (e.g.,cache memory or system memory) and execution unit array 414. In someembodiments, sampling engine 430 provides a memory access mechanism forexecution unit array 414 that allows execution array 414 to readgraphics and media data from memory. In some embodiments, samplingengine 430 includes logic to perform specialized image samplingoperations for media.

In some embodiments, the specialized media sampling logic in samplingengine 430 includes a de-noise/de-interlace module 432, a motionestimation module 434, and an image scaling and filtering module 436. Insome embodiments, de-noise/de-interlace module 432 includes logic toperform one or more of a de-noise or a de-interlace algorithm on decodedvideo data. The de-interlace logic combines alternating fields ofinterlaced video content into a single fame of video. The de-noise logicreduces or removes data noise from video and image data. In someembodiments, the de-noise logic and de-interlace logic are motionadaptive and use spatial or temporal filtering based on the amount ofmotion detected in the video data. In some embodiments, thede-noise/de-interlace module 432 includes dedicated motion detectionlogic (e.g., within the motion estimation engine 434).

In some embodiments, motion estimation engine 434 provides hardwareacceleration for video operations by performing video accelerationfunctions such as motion vector estimation and prediction on video data.The motion estimation engine determines motion vectors that describe thetransformation of image data between successive video frames. In someembodiments, a graphics processor media codec uses video motionestimation engine 434 to perform operations on video at the macro-blocklevel that may otherwise be too computationally intensive to performwith a general-purpose processor. In some embodiments, motion estimationengine 434 is generally available to graphics processor components toassist with video decode and processing functions that are sensitive oradaptive to the direction or magnitude of the motion within video data.

In some embodiments, image scaling and filtering module 436 performsimage-processing operations to enhance the visual quality of generatedimages and video. In some embodiments, scaling and filtering module 436processes image and video data during the sampling operation beforeproviding the data to execution unit array 414.

In some embodiments, the GPE 410 includes a data port 444, whichprovides an additional mechanism for graphics subsystems to accessmemory. In some embodiments, data port 444 facilitates memory access foroperations including render target writes, constant buffer reads,scratch memory space reads/writes, and media surface accesses. In someembodiments, data port 444 includes cache memory space to cache accessesto memory. The cache memory can be a single data cache or separated intomultiple caches for the multiple subsystems that access memory via thedata port (e.g., a render buffer cache, a constant buffer cache, etc.).In some embodiments, threads executing on an execution unit in executionunit array 414 communicate with the data port by exchanging messages viaa data distribution interconnect that couples each of the sub-systems ofGPE 410.

Execution Units

FIG. 5 is a block diagram of another embodiment of a graphics processor500. Elements of FIG. 5 having the same reference numbers (or names) asthe elements of any other figure herein can operate or function in anymanner similar to that described elsewhere herein, but are not limitedto such.

In some embodiments, graphics processor 500 includes a ring interconnect502, a pipeline front-end 504, a media engine 537, and graphics cores580A-580N. In some embodiments, ring interconnect 502 couples thegraphics processor to other processing units, including other graphicsprocessors or one or more general-purpose processor cores. In someembodiments, the graphics processor is one of many processors integratedwithin a multi-core processing system.

In some embodiments, graphics processor 500 receives batches of commandsvia ring interconnect 502. The incoming commands are interpreted by acommand streamer 503 in the pipeline front-end 504. In some embodiments,graphics processor 500 includes scalable execution logic to perform 3Dgeometry processing and media processing via the graphics core(s)580A-580N. For 3D geometry processing commands, command streamer 503supplies commands to geometry pipeline 536. For at least some mediaprocessing commands, command streamer 503 supplies the commands to avideo front end 534, which couples with a media engine 537. In someembodiments, media engine 537 includes a Video Quality Engine (VQE) 530for video and image post-processing and a multi-format encode/decode(MFX) 533 engine to provide hardware-accelerated media data encode anddecode. In some embodiments, geometry pipeline 536 and media engine 537each generate execution threads for the thread execution resourcesprovided by at least one graphics core 580A.

In some embodiments, graphics processor 500 includes scalable threadexecution resources featuring modular cores 580A-580N (sometimesreferred to as core slices), each having multiple sub-cores 550A-550N,560A-560N (sometimes referred to as core sub-slices). In someembodiments, graphics processor 500 can have any number of graphicscores 580A through 580N. In some embodiments, graphics processor 500includes a graphics core 580A having at least a first sub-core 550A anda second core sub-core 560A. In other embodiments, the graphicsprocessor is a low power processor with a single sub-core (e.g., 550A).In some embodiments, graphics processor 500 includes multiple graphicscores 580A-580N, each including a set of first sub-cores 550A-550N and aset of second sub-cores 560A-560N. Each sub-core in the set of firstsub-cores 550A-550N includes at least a first set of execution units552A-552N and media/texture samplers 554A-554N. Each sub-core in the setof second sub-cores 560A-560N includes at least a second set ofexecution units 562A-562N and samplers 564A-564N. In some embodiments,each sub-core 550A-550N, 560A-560N shares a set of shared resources570A-570N. In some embodiments, the shared resources include sharedcache memory and pixel operation logic. Other shared resources may alsobe included in the various embodiments of the graphics processor.

FIG. 6 illustrates thread execution logic 600 including an array ofprocessing elements employed in some embodiments of a GPE. Elements ofFIG. 6 having the same reference numbers (or names) as the elements ofany other figure herein can operate or function in any manner similar tothat described elsewhere herein, but are not limited to such.

In some embodiments, thread execution logic 600 includes a pixel shader602, a thread dispatcher 604, instruction cache 606, a scalableexecution unit array including a plurality of execution units 608A-608N,a sampler 610, a data cache 612, and a data port 614. In one embodimentthe included components are interconnected via an interconnect fabricthat links to each of the components. In some embodiments, threadexecution logic 600 includes one or more connections to memory, such assystem memory or cache memory, through one or more of instruction cache606, data port 614, sampler 610, and execution unit array 608A-608N. Insome embodiments, each execution unit (e.g. 608A) is an individualvector processor capable of executing multiple simultaneous threads andprocessing multiple data elements in parallel for each thread. In someembodiments, execution unit array 608A-608N includes any numberindividual execution units.

In some embodiments, execution unit array 608A-608N is primarily used toexecute “shader” programs. In some embodiments, the execution units inarray 608A-608N execute an instruction set that includes native supportfor many standard 3D graphics shader instructions, such that shaderprograms from graphics libraries (e.g., Direct 3D and OpenGL) areexecuted with a minimal translation. The execution units support vertexand geometry processing (e.g., vertex programs, geometry programs,vertex shaders), pixel processing (e.g., pixel shaders, fragmentshaders) and general-purpose processing (e.g., compute and mediashaders).

Each execution unit in execution unit array 608A-608N operates on arraysof data elements. The number of data elements is the “execution size,”or the number of channels for the instruction. An execution channel is alogical unit of execution for data element access, masking, and flowcontrol within instructions. The number of channels may be independentof the number of physical Arithmetic Logic Units (ALUs) or FloatingPoint Units (FPUs) for a particular graphics processor. In someembodiments, execution units 608A-608N support integer andfloating-point data types.

The execution unit instruction set includes single instruction multipledata (SIMD) instructions. The various data elements can be stored as apacked data type in a register and the execution unit will process thevarious elements based on the data size of the elements. For example,when operating on a 256-bit wide vector, the 256 bits of the vector arestored in a register and the execution unit operates on the vector asfour separate 64-bit packed data elements (Quad-Word (QW) size dataelements), eight separate 32-bit packed data elements (Double Word (DW)size data elements), sixteen separate 16-bit packed data elements (Word(W) size data elements), or thirty-two separate 8-bit data elements(byte (B) size data elements). However, different vector widths andregister sizes are possible.

One or more internal instruction caches (e.g., 606) are included in thethread execution logic 600 to cache thread instructions for theexecution units. In some embodiments, one or more data caches (e.g.,612) are included to cache thread data during thread execution. In someembodiments, sampler 610 is included to provide texture sampling for 3Doperations and media sampling for media operations. In some embodiments,sampler 610 includes specialized texture or media sampling functionalityto process texture or media data during the sampling process beforeproviding the sampled data to an execution unit.

During execution, the graphics and media pipelines send threadinitiation requests to thread execution logic 600 via thread spawningand dispatch logic. In some embodiments, thread execution logic 600includes a local thread dispatcher 604 that arbitrates thread initiationrequests from the graphics and media pipelines and instantiates therequested threads on one or more execution units 608A-608N. For example,the geometry pipeline (e.g., 536 of FIG. 5) dispatches vertexprocessing, tessellation, or geometry processing threads to threadexecution logic 600 (FIG. 6). In some embodiments, thread dispatcher 604can also process runtime thread spawning requests from the executingshader programs.

Once a group of geometric objects has been processed and rasterized intopixel data, pixel shader 602 is invoked to further compute outputinformation and cause results to be written to output surfaces (e.g.,color buffers, depth buffers, stencil buffers, etc.). In someembodiments, pixel shader 602 calculates the values of the variousvertex attributes that are to be interpolated across the rasterizedobject. In some embodiments, pixel shader 602 then executes anapplication programming interface (API)-supplied pixel shader program.To execute the pixel shader program, pixel shader 602 dispatches threadsto an execution unit (e.g., 608A) via thread dispatcher 604. In someembodiments, pixel shader 602 uses texture sampling logic in sampler 610to access texture data in texture maps stored in memory. Arithmeticoperations on the texture data and the input geometry data compute pixelcolor data for each geometric fragment, or discards one or more pixelsfrom further processing.

In some embodiments, the data port 614 provides a memory accessmechanism for the thread execution logic 600 output processed data tomemory for processing on a graphics processor output pipeline. In someembodiments, the data port 614 includes or couples to one or more cachememories (e.g., data cache 612) to cache data for memory access via thedata port.

FIG. 7 is a block diagram illustrating a graphics processor instructionformats 700 according to some embodiments. In one or more embodiment,the graphics processor execution units support an instruction set havinginstructions in multiple formats. The solid lined boxes illustrate thecomponents that are generally included in an execution unit instruction,while the dashed lines include components that are optional or that areonly included in a sub-set of the instructions. In some embodiments,instruction format 700 described and illustrated are macro-instructions,in that they are instructions supplied to the execution unit, as opposedto micro-operations resulting from instruction decode once theinstruction is processed.

In some embodiments, the graphics processor execution units nativelysupport instructions in a 128-bit format 710. A 64-bit compactedinstruction format 730 is available for some instructions based on theselected instruction, instruction options, and number of operands. Thenative 128-bit format 710 provides access to all instruction options,while some options and operations are restricted in the 64-bit format730. The native instructions available in the 64-bit format 730 vary byembodiment. In some embodiments, the instruction is compacted in partusing a set of index values in an index field 713. The execution unithardware references a set of compaction tables based on the index valuesand uses the compaction table outputs to reconstruct a nativeinstruction in the 128-bit format 710.

For each format, instruction opcode 712 defines the operation that theexecution unit is to perform. The execution units execute eachinstruction in parallel across the multiple data elements of eachoperand. For example, in response to an add instruction the executionunit performs a simultaneous add operation across each color channelrepresenting a texture element or picture element. By default, theexecution unit performs each instruction across all data channels of theoperands. In some embodiments, instruction control field 714 enablescontrol over certain execution options, such as channels selection(e.g., predication) and data channel order (e.g., swizzle). For 128-bitinstructions 710 an exec-size field 716 limits the number of datachannels that will be executed in parallel. In some embodiments,exec-size field 716 is not available for use in the 64-bit compactinstruction format 730.

Some execution unit instructions have up to three operands including twosource operands, src0 722, src1 722, and one destination 718. In someembodiments, the execution units support dual destination instructions,where one of the destinations is implied. Data manipulation instructionscan have a third source operand (e.g., SRC2 724), where the instructionopcode 712 determines the number of source operands. An instruction'slast source operand can be an immediate (e.g., hard-coded) value passedwith the instruction.

In some embodiments, the 128-bit instruction format 710 includes anaccess/address mode information 726 specifying, for example, whetherdirect register addressing mode or indirect register addressing mode isused. When direct register addressing mode is used, the register addressof one or more operands is directly provided by bits in the instruction710.

In some embodiments, the 128-bit instruction format 710 includes anaccess/address mode field 726, which specifies an address mode and/or anaccess mode for the instruction. In one embodiment the access mode todefine a data access alignment for the instruction. Some embodimentssupport access modes including a 16-byte aligned access mode and a1-byte aligned access mode, where the byte alignment of the access modedetermines the access alignment of the instruction operands. Forexample, when in a first mode, the instruction 710 may use byte-alignedaddressing for source and destination operands and when in a secondmode, the instruction 710 may use 16-byte-aligned addressing for allsource and destination operands.

In one embodiment, the address mode portion of the access/address modefield 726 determines whether the instruction is to use direct orindirect addressing. When direct register addressing mode is used bitsin the instruction 710 directly provide the register address of one ormore operands. When indirect register addressing mode is used, theregister address of one or more operands may be computed based on anaddress register value and an address immediate field in theinstruction.

In some embodiments instructions are grouped based on opcode 712bit-fields to simplify Opcode decode 740. For an 8-bit opcode, bits 4,5, and 6 allow the execution unit to determine the type of opcode. Theprecise opcode grouping shown is merely an example. In some embodiments,a move and logic opcode group 742 includes data movement and logicinstructions (e.g., move (mov), compare (cmp)). In some embodiments,move and logic group 742 shares the five most significant bits (MSB),where move (mov) instructions are in the form of 0000xxxxb and logicinstructions are in the form of 0001xxxxb. A flow control instructiongroup 744 (e.g., call, jump (jmp)) includes instructions in the form of0010xxxxb (e.g., 0x20). A miscellaneous instruction group 746 includes amix of instructions, including synchronization instructions (e.g., wait,send) in the form of 0011xxxxb (e.g., 0x30). A parallel math instructiongroup 748 includes component-wise arithmetic instructions (e.g., add,multiply (mul)) in the form of 0100xxxxb (e.g., 0x40). The parallel mathgroup 748 performs the arithmetic operations in parallel across datachannels. The vector math group 750 includes arithmetic instructions(e.g., dp4) in the form of 0101xxxxb (e.g., 0x50). The vector math groupperforms arithmetic such as dot product calculations on vector operands.

Graphics Pipeline

FIG. 8 is a block diagram of another embodiment of a graphics processor800. Elements of FIG. 8 having the same reference numbers (or names) asthe elements of any other figure herein can operate or function in anymanner similar to that described elsewhere herein, but are not limitedto such.

In some embodiments, graphics processor 800 includes a graphics pipeline820, a media pipeline 830, a display engine 840, thread execution logic850, and a render output pipeline 870. In some embodiments, graphicsprocessor 800 is a graphics processor within a multi-core processingsystem that includes one or more general purpose processing cores. Thegraphics processor is controlled by register writes to one or morecontrol registers (not shown) or via commands issued to graphicsprocessor 800 via a ring interconnect 802. In some embodiments, ringinterconnect 802 couples graphics processor 800 to other processingcomponents, such as other graphics processors or general-purposeprocessors. Commands from ring interconnect 802 are interpreted by acommand streamer 803, which supplies instructions to individualcomponents of graphics pipeline 820 or media pipeline 830.

In some embodiments, command streamer 803 directs the operation of avertex fetcher 805 that reads vertex data from memory and executesvertex-processing commands provided by command streamer 803. In someembodiments, vertex fetcher 805 provides vertex data to a vertex shader807, which performs coordinate space transformation and lightingoperations to each vertex. In some embodiments, vertex fetcher 805 andvertex shader 807 execute vertex-processing instructions by dispatchingexecution threads to execution units 852A, 852B via a thread dispatcher831.

In some embodiments, execution units 852A, 852B are an array of vectorprocessors having an instruction set for performing graphics and mediaoperations. In some embodiments, execution units 852A, 852B have anattached L1 cache 851 that is specific for each array or shared betweenthe arrays. The cache can be configured as a data cache, an instructioncache, or a single cache that is partitioned to contain data andinstructions in different partitions.

In some embodiments, graphics pipeline 820 includes tessellationcomponents to perform hardware-accelerated tessellation of 3D objects.In some embodiments, a programmable hull shader 811 configures thetessellation operations. A programmable domain shader 817 providesback-end evaluation of tessellation output. A tessellator 813 operatesat the direction of hull shader 811 and contains special purpose logicto generate a set of detailed geometric objects based on a coarsegeometric model that is provided as input to graphics pipeline 820. Insome embodiments, if tessellation is not used, tessellation components811, 813, 817 can be bypassed.

In some embodiments, complete geometric objects can be processed by ageometry shader 819 via one or more threads dispatched to executionunits 852A, 852B, or can proceed directly to the clipper 829. In someembodiments, the geometry shader operates on entire geometric objects,rather than vertices or patches of vertices as in previous stages of thegraphics pipeline. If the tessellation is disabled the geometry shader819 receives input from the vertex shader 807. In some embodiments,geometry shader 819 is programmable by a geometry shader program toperform geometry tessellation if the tessellation units are disabled.

Before rasterization, a clipper 829 processes vertex data. The clipper829 may be a fixed function clipper or a programmable clipper havingclipping and geometry shader functions. In some embodiments, arasterizer and depth test component 873 in the render output pipeline870 dispatches pixel shaders to convert the geometric objects into theirper pixel representations. In some embodiments, pixel shader logic isincluded in thread execution logic 850. In some embodiments, anapplication can bypass the rasterizer 873 and access un-rasterizedvertex data via a stream out unit 823.

The graphics processor 800 has an interconnect bus, interconnect fabric,or some other interconnect mechanism that allows data and messagepassing amongst the major components of the processor. In someembodiments, execution units 852A, 852B and associated cache(s) 851,texture and media sampler 854, and texture/sampler cache 858interconnect via a data port 856 to perform memory access andcommunicate with render output pipeline components of the processor. Insome embodiments, sampler 854, caches 851, 858 and execution units 852A,852B each have separate memory access paths.

In some embodiments, render output pipeline 870 contains a rasterizerand depth test component 873 that converts vertex-based objects into anassociated pixel-based representation. In some embodiments, therasterizer logic includes a windower/masker unit to perform fixedfunction triangle and line rasterization. An associated render cache 878and depth cache 879 are also available in some embodiments. A pixeloperations component 877 performs pixel-based operations on the data,though in some instances, pixel operations associated with 2D operations(e.g. bit block image transfers with blending) are performed by the 2Dengine 841, or substituted at display time by the display controller 843using overlay display planes. In some embodiments, a shared L3 cache 875is available to all graphics components, allowing the sharing of datawithout the use of main system memory.

In some embodiments, graphics processor media pipeline 830 includes amedia engine 837 and a video front end 834. In some embodiments, videofront end 834 receives pipeline commands from the command streamer 803.In some embodiments, media pipeline 830 includes a separate commandstreamer. In some embodiments, video front-end 834 processes mediacommands before sending the command to the media engine 837. In someembodiments, media engine 337 includes thread spawning functionality tospawn threads for dispatch to thread execution logic 850 via threaddispatcher 831.

In some embodiments, graphics processor 800 includes a display engine840. In some embodiments, display engine 840 is external to processor800 and couples with the graphics processor via the ring interconnect802, or some other interconnect bus or fabric. In some embodiments,display engine 840 includes a 2D engine 841 and a display controller843. In some embodiments, display engine 840 contains special purposelogic capable of operating independently of the 3D pipeline. In someembodiments, display controller 843 couples with a display device (notshown), which may be a system integrated display device, as in a laptopcomputer, or an external display device attached via a display deviceconnector.

In some embodiments, graphics pipeline 820 and media pipeline 830 areconfigurable to perform operations based on multiple graphics and mediaprogramming interfaces and are not specific to any one applicationprogramming interface (API). In some embodiments, driver software forthe graphics processor translates API calls that are specific to aparticular graphics or media library into commands that can be processedby the graphics processor. In some embodiments, support is provided forthe Open Graphics Library (OpenGL) and Open Computing Language (OpenCL)from the Khronos Group, the Direct3D library from the MicrosoftCorporation, or support may be provided to both OpenGL and D3D. Supportmay also be provided for the Open Source Computer Vision Library(OpenCV). A future API with a compatible 3D pipeline would also besupported if a mapping can be made from the pipeline of the future APIto the pipeline of the graphics processor.

Graphics Pipeline Programming

FIG. 9A is a block diagram illustrating a graphics processor commandformat 900 according to some embodiments. FIG. 9B is a block diagramillustrating a graphics processor command sequence 910 according to anembodiment. The solid lined boxes in FIG. 9A illustrate the componentsthat are generally included in a graphics command while the dashed linesinclude components that are optional or that are only included in asub-set of the graphics commands. The exemplary graphics processorcommand format 900 of FIG. 9A includes data fields to identify a targetclient 902 of the command, a command operation code (opcode) 904, andthe relevant data 906 for the command. A sub-opcode 905 and a commandsize 908 are also included in some commands.

In some embodiments, client 902 specifies the client unit of thegraphics device that processes the command data. In some embodiments, agraphics processor command parser examines the client field of eachcommand to condition the further processing of the command and route thecommand data to the appropriate client unit. In some embodiments, thegraphics processor client units include a memory interface unit, arender unit, a 2D unit, a 3D unit, and a media unit. Each client unithas a corresponding processing pipeline that processes the commands.Once the command is received by the client unit, the client unit readsthe opcode 904 and, if present, sub-opcode 905 to determine theoperation to perform. The client unit performs the command usinginformation in data field 906. For some commands an explicit commandsize 908 is expected to specify the size of the command. In someembodiments, the command parser automatically determines the size of atleast some of the commands based on the command opcode. In someembodiments commands are aligned via multiples of a double word.

The flow diagram in FIG. 9B shows an exemplary graphics processorcommand sequence 910. In some embodiments, software or firmware of adata processing system that features an embodiment of a graphicsprocessor uses a version of the command sequence shown to set up,execute, and terminate a set of graphics operations. A sample commandsequence is shown and described for purposes of example only asembodiments are not limited to these specific commands or to thiscommand sequence. Moreover, the commands may be issued as batch ofcommands in a command sequence, such that the graphics processor willprocess the sequence of commands in at least partially concurrence.

In some embodiments, the graphics processor command sequence 910 maybegin with a pipeline flush command 912 to cause any active graphicspipeline to complete the currently pending commands for the pipeline. Insome embodiments, the 3D pipeline 922 and the media pipeline 924 do notoperate concurrently. The pipeline flush is performed to cause theactive graphics pipeline to complete any pending commands. In responseto a pipeline flush, the command parser for the graphics processor willpause command processing until the active drawing engines completepending operations and the relevant read caches are invalidated.Optionally, any data in the render cache that is marked ‘dirty’ can beflushed to memory. In some embodiments, pipeline flush command 912 canbe used for pipeline synchronization or before placing the graphicsprocessor into a low power state.

In some embodiments, a pipeline select command 913 is used when acommand sequence requires the graphics processor to explicitly switchbetween pipelines. In some embodiments, a pipeline select command 913 isrequired only once within an execution context before issuing pipelinecommands unless the context is to issue commands for both pipelines. Insome embodiments, a pipeline flush command is 912 is requiredimmediately before a pipeline switch via the pipeline select command913.

In some embodiments, a pipeline control command 914 configures agraphics pipeline for operation and is used to program the 3D pipeline922 and the media pipeline 924. In some embodiments, pipeline controlcommand 914 configures the pipeline state for the active pipeline. Inone embodiment, the pipeline control command 914 is used for pipelinesynchronization and to clear data from one or more cache memories withinthe active pipeline before processing a batch of commands.

In some embodiments, return buffer state commands 916 are used toconfigure a set of return buffers for the respective pipelines to writedata. Some pipeline operations require the allocation, selection, orconfiguration of one or more return buffers into which the operationswrite intermediate data during processing. In some embodiments, thegraphics processor also uses one or more return buffers to store outputdata and to perform cross thread communication. In some embodiments, thereturn buffer state 916 includes selecting the size and number of returnbuffers to use for a set of pipeline operations.

The remaining commands in the command sequence differ based on theactive pipeline for operations. Based on a pipeline determination 920,the command sequence is tailored to the 3D pipeline 922 beginning withthe 3D pipeline state 930, or the media pipeline 924 beginning at themedia pipeline state 940.

The commands for the 3D pipeline state 930 include 3D state settingcommands for vertex buffer state, vertex element state, constant colorstate, depth buffer state, and other state variables that are to beconfigured before 3D primitive commands are processed. The values ofthese commands are determined at least in part based the particular 3DAPI in use. In some embodiments, 3D pipeline state 930 commands are alsoable to selectively disable or bypass certain pipeline elements if thoseelements will not be used.

In some embodiments, 3D primitive 932 command is used to submit 3Dprimitives to be processed by the 3D pipeline. Commands and associatedparameters that are passed to the graphics processor via the 3Dprimitive 932 command are forwarded to the vertex fetch function in thegraphics pipeline. The vertex fetch function uses the 3D primitive 932command data to generate vertex data structures. The vertex datastructures are stored in one or more return buffers. In someembodiments, 3D primitive 932 command is used to perform vertexoperations on 3D primitives via vertex shaders. To process vertexshaders, 3D pipeline 922 dispatches shader execution threads to graphicsprocessor execution units.

In some embodiments, 3D pipeline 922 is triggered via an execute 934command or event. In some embodiments, a register write triggers commandexecution. In some embodiments execution is triggered via a ‘go’ or‘kick’ command in the command sequence. In one embodiment commandexecution is triggered using a pipeline synchronization command to flushthe command sequence through the graphics pipeline. The 3D pipeline willperform geometry processing for the 3D primitives. Once operations arecomplete, the resulting geometric objects are rasterized and the pixelengine colors the resulting pixels. Additional commands to control pixelshading and pixel back end operations may also be included for thoseoperations.

In some embodiments, the graphics processor command sequence 910 followsthe media pipeline 924 path when performing media operations. Ingeneral, the specific use and manner of programming for the mediapipeline 924 depends on the media or compute operations to be performed.Specific media decode operations may be offloaded to the media pipelineduring media decode. In some embodiments, the media pipeline can also bebypassed and media decode can be performed in whole or in part usingresources provided by one or more general purpose processing cores. Inone embodiment, the media pipeline also includes elements forgeneral-purpose graphics processor unit (GPGPU) operations, where thegraphics processor is used to perform SIMD vector operations usingcomputational shader programs that are not explicitly related to therendering of graphics primitives.

In some embodiments, media pipeline 924 is configured in a similarmanner as the 3D pipeline 922. A set of media pipeline state commands940 are dispatched or placed into in a command queue before the mediaobject commands 942. In some embodiments, media pipeline state commands940 include data to configure the media pipeline elements that will beused to process the media objects. This includes data to configure thevideo decode and video encode logic within the media pipeline, such asencode or decode format. In some embodiments, media pipeline statecommands 940 also support the use one or more pointers to “indirect”state elements that contain a batch of state settings.

In some embodiments, media object commands 942 supply pointers to mediaobjects for processing by the media pipeline. The media objects includememory buffers containing video data to be processed. In someembodiments, all media pipeline states must be valid before issuing amedia object command 942. Once the pipeline state is configured andmedia object commands 942 are queued, the media pipeline 924 istriggered via an execute command 944 or an equivalent execute event(e.g., register write). Output from media pipeline 924 may then be postprocessed by operations provided by the 3D pipeline 922 or the mediapipeline 924. In some embodiments, GPGPU operations are configured andexecuted in a similar manner as media operations.

Graphics Software Architecture

FIG. 10 illustrates exemplary graphics software architecture for a dataprocessing system 1000 according to some embodiments. In someembodiments, software architecture includes a 3D graphics application1010, an operating system 1020, and at least one processor 1030. In someembodiments, processor 1030 includes a graphics processor 1032 and oneor more general-purpose processor core(s) 1034. The graphics application1010 and operating system 1020 each execute in the system memory 1050 ofthe data processing system.

In some embodiments, 3D graphics application 1010 contains one or moreshader programs including shader instructions 1012. The shader languageinstructions may be in a high-level shader language, such as the HighLevel Shader Language (HLSL) or the OpenGL Shader Language (GLSL). Theapplication also includes executable instructions 1014 in a machinelanguage suitable for execution by the general-purpose processor core1034. The application also includes graphics objects 1016 defined byvertex data.

In some embodiments, operating system 1020 is a Microsoft® Windows®operating system from the Microsoft Corporation, a proprietary UNIX-likeoperating system, or an open source UNIX-like operating system using avariant of the Linux kernel. When the Direct3D API is in use, theoperating system 1020 uses a front-end shader compiler 1024 to compileany shader instructions 1012 in HLSL into a lower-level shader language.The compilation may be a just-in-time (JIT) compilation or theapplication can perform shader pre-compilation. In some embodiments,high-level shaders are compiled into low-level shaders during thecompilation of the 3D graphics application 1010.

In some embodiments, user mode graphics driver 1026 contains a back-endshader compiler 1027 to convert the shader instructions 1012 into ahardware specific representation. When the OpenGL API is in use, shaderinstructions 1012 in the GLSL high-level language are passed to a usermode graphics driver 1026 for compilation. In some embodiments, usermode graphics driver 1026 uses operating system kernel mode functions1028 to communicate with a kernel mode graphics driver 1029. In someembodiments, kernel mode graphics driver 1029 communicates with graphicsprocessor 1032 to dispatch commands and instructions.

IP Core Implementations

One or more aspects of at least one embodiment may be implemented byrepresentative code stored on a machine-readable medium which representsand/or defines logic within an integrated circuit such as a processor.For example, the machine-readable medium may include instructions whichrepresent various logic within the processor. When read by a machine,the instructions may cause the machine to fabricate the logic to performthe techniques described herein. Such representations, known as “IPcores,” are reusable units of logic for an integrated circuit that maybe stored on a tangible, machine-readable medium as a hardware modelthat describes the structure of the integrated circuit. The hardwaremodel may be supplied to various customers or manufacturing facilities,which load the hardware model on fabrication machines that manufacturethe integrated circuit. The integrated circuit may be fabricated suchthat the circuit performs operations described in association with anyof the embodiments described herein.

FIG. 11 is a block diagram illustrating an IP core development system1100 that may be used to manufacture an integrated circuit to performoperations according to an embodiment. The IP core development system1100 may be used to generate modular, re-usable designs that can beincorporated into a larger design or used to construct an entireintegrated circuit (e.g., an SOC integrated circuit). A design facility1130 can generate a software simulation 1110 of an IP core design in ahigh level programming language (e.g., C/C++). The software simulation1110 can be used to design, test, and verify the behavior of the IPcore. A register transfer level (RTL) design can then be created orsynthesized from the simulation model 1100. The RTL design 1115 is anabstraction of the behavior of the integrated circuit that models theflow of digital signals between hardware registers, including theassociated logic performed using the modeled digital signals. Inaddition to an RTL design 1115, lower-level designs at the logic levelor transistor level may also be created, designed, or synthesized. Thus,the particular details of the initial design and simulation may vary.

The RTL design 1115 or equivalent may be further synthesized by thedesign facility into a hardware model 1120, which may be in a hardwaredescription language (HDL), or some other representation of physicaldesign data. The HDL may be further simulated or tested to verify the IPcore design. The IP core design can be stored for delivery to a 3^(rd)party fabrication facility 1165 using non-volatile memory 1140 (e.g.,hard disk, flash memory, or any non-volatile storage medium).Alternatively, the IP core design may be transmitted (e.g., via theInternet) over a wired connection 1150 or wireless connection 1160. Thefabrication facility 1165 may then fabricate an integrated circuit thatis based at least in part on the IP core design. The fabricatedintegrated circuit can be configured to perform operations in accordancewith at least one embodiment described herein.

FIG. 12 is a block diagram illustrating an exemplary system on a chipintegrated circuit 1200 that may be fabricated using one or more IPcores, according to an embodiment. The exemplary integrated circuitincludes one or more application processors 1205 (e.g., CPUs), at leastone graphics processor 1210, and may additionally include an imageprocessor 1215 and/or a video processor 1220, any of which may be amodular IP core from the same or multiple different design facilities.The integrated circuit includes peripheral or bus logic including a USBcontroller 1225, UART controller 1230, an SPI/SDIO controller 1235, andan I²S/I²C controller 1240. Additionally, the integrated circuit caninclude a display device 1245 coupled to one or more of ahigh-definition multimedia interface (HDMI) controller 1250 and a mobileindustry processor interface (MIPI) display interface 1255. Storage maybe provided by a flash memory subsystem 1260 including flash memory anda flash memory controller. Memory interface may be provided via a memorycontroller 1265 for access to SDRAM or SRAM memory devices. Someintegrated circuits additionally include an embedded security engine1270.

Additionally, other logic and circuits may be included in the processorof integrated circuit 1200, including additional graphicsprocessors/cores, peripheral interface controllers, or general purposeprocessor cores.

FIG. 13 illustrates a computing device 1300 employing a real-timeselective data compression mechanism 1300 according to one embodiment.Computing device 1300 (e.g., mobile computer, laptop computer, desktopcomputer, etc.) may be the same as data processing system 100 of FIG. 1and accordingly, for brevity and ease of understanding, many of thedetails stated above with reference to FIGS. 1-12 are not furtherdiscussed or repeated hereafter. For example, computing device 1300 mayinclude a mobile computer (e.g., smartphone, tablet computer, laptops,game consoles, portable workstations, smart glasses and other smartwearable devices, etc.) serving as a host machine for hosting real-timeselective data compression mechanism (“compression mechanism”) 1310.

Compression mechanism 1310 may include any number and type of componentsfor facilitating lossy compression of selective data based on real-timesensory data relating to the user and/or the surrounding environment forachieving continuous efficient rending of display contents withoutcompromising the user experience according to one embodiment. Throughoutthe document, the term “user” may be interchangeably referred to as“viewer”, “observer”, “person”, “individual”, “end-user”, and/or thelike. It is to be noted that throughout this document, terms like“graphics domain” may be referenced interchangeably with “graphicsprocessing unit” or simply “GPU” and similarly, “CPU domain” or “hostdomain” may be referenced interchangeably with “computer processingunit” or simply “CPU”.

Computing device 1300 may include any number and type of communicationdevices, such as large computing systems, such as server computers,desktop computers, etc., and may further include set-top boxes (e.g.,Internet-based cable television set-top boxes, etc.), global positioningsystem (GPS)-based devices, etc. Computing device 1300 may includemobile computing devices serving as communication devices, such ascellular phones including smartphones, personal digital assistants(PDAs), tablet computers, laptop computers, e-readers, smarttelevisions, television platforms, wearable devices (e.g., glasses,watches, bracelets, smartcards, jewelry, clothing items, etc.), mediaplayers, etc. For example, in one embodiment, computing device 1300 mayinclude a mobile computing device employing an integrated circuit(“IC”), such as system on a chip (“SoC” or “SOC”), integrating varioushardware and/or software components of computing device 1300 on a singlechip.

As illustrated, in one embodiment, in addition to employing compressionmechanism 1310, computing device 1300 may further include any number andtype of hardware components and/or software components, such as (but notlimited to) GPU 1314 (having driver logic 1316), CPU 1312, memory 1308,network devices, drivers, or the like, as well as input/output (I/O)sources 1304, such as touchscreens, touch panels, touch pads, virtual orregular keyboards, virtual or regular mice, ports, connectors, etc.Computing device 1300 may include operating system (OS) 1306 serving asan interface between hardware and/or physical resources of the computerdevice 1300 and a user. It is contemplated that CPU 1312 may include oneor processors, such as processor(s) 102 of FIG. 1, while GPU 1314 mayinclude one or more graphics processors, such as graphics processor(s)108 of FIG. 1. In one embodiment and as will be further descried withreference to the subsequent figures, compression mechanism 1310 may bein communication with its host driver logic 1316 which cooperates withGPU 1314 to facilitate any number and type of tasks facilitatinggeneration and rendering of virtual 3D images as is described throughthis document.

It is to be noted that terms like “node”, “computing node”, “server”,“server device”, “cloud computer”, “cloud server”, “cloud servercomputer”, “machine”, “host machine”, “device”, “computing device”,“computer”, “computing system”, and the like, may be usedinterchangeably throughout this document. It is to be further noted thatterms like “application”, “software application”, “program”, “softwareprogram”, “package”, “software package”, and the like, may be usedinterchangeably throughout this document. Also, terms like “job”,“input”, “request”, “message”, and the like, may be used interchangeablythroughout this document.

It is contemplated and as further described with reference to FIGS.1-12, some processes of the graphics pipeline as described above areimplemented in software, while the rest are implemented in hardware. Agraphics pipeline may be implemented in a graphics coprocessor design,where CPU 1312 is designed to work with GPU 1314 which may be includedin or co-located with CPU 1312. In one embodiment, GPU 1314 may employany number and type of conventional software and hardware logic toperform the conventional functions relating to graphics rendering aswell as novel software and hardware logic to execute any number and typeof instructions, such as instructions 121 of FIG. 1, to perform thevarious novel functions of compression mechanism 1310 as disclosedthroughout this document.

As aforementioned, memory 1308 may include a random access memory (RAM)comprising application database having object information. A memorycontroller hub, such as memory controller hub 116 of FIG. 1, may accessdata in the RAM and forward it to GPU 1314 for graphics pipelineprocessing. RAM may include double data rate RAM (DDR RAM), extendeddata output RAM (EDO RAM), etc. CPU 1312 interacts with a hardwaregraphics pipeline, as illustrated with reference to FIG. 3, to sharegraphics pipelining functionality. Processed data is stored in a bufferin the hardware graphics pipeline, and state information is stored inmemory 1308. The resulting image is then transferred to I/O sources1304, such as a display component, such as display device 320 of FIG. 3,for displaying of the image. It is contemplated that the display devicemay be of various types, such as Cathode Ray Tube (CRT), Thin FilmTransistor (TFT), Liquid Crystal Display (LCD), Organic Light EmittingDiode (OLED) array, etc., to display information to a user.

Memory 1308 may comprise a pre-allocated region of a buffer (e.g., framebuffer); however, it should be understood by one of ordinary skill inthe art that the embodiments are not so limited, and that any memoryaccessible to the lower graphics pipeline may be used. Computing device1300 may further include input/output (I/O) control hub (ICH) 130 asreferenced in FIG. 1, one or more I/O sources 1304, etc.

CPU 1312 may include one or more processors to execute instructions inorder to perform whatever software routines the computing systemimplements. The instructions frequently involve some sort of operationperformed upon data. Both data and instructions may be stored in systemmemory 1308 and any associated cache. Cache is typically designed tohave shorter latency times than system memory 1308; for example, cachemight be integrated onto the same silicon chip(s) as the processor(s)and/or constructed with faster static RAM (SRAM) cells whilst the systemmemory 1308 might be constructed with slower dynamic RAM (DRAM) cells.By tending to store more frequently used instructions and data in thecache as opposed to the system memory 1308, the overall performanceefficiency of computing device 1300 improves. It is contemplated that insome embodiments, GPU 1314 may exist as part of CPU 1312 (such as partof a physical CPU package) in which case, memory 1308 may be shared byCPU 1312 and GPU 1314 or kept separated.

System memory 1308 may be made available to other components within thecomputing device 1300. For example, any data (e.g., input graphics data)received from various interfaces to the computing device 1300 (e.g.,keyboard and mouse, printer port, Local Area Network (LAN) port, modemport, etc.) or retrieved from an internal storage element of thecomputer device 1300 (e.g., hard disk drive) are often temporarilyqueued into system memory 1308 prior to their being operated upon by theone or more processor(s) in the implementation of a software program.Similarly, data that a software program determines should be sent fromthe computing device 1300 to an outside entity through one of thecomputing system interfaces, or stored into an internal storage element,is often temporarily queued in system memory 1308 prior to its beingtransmitted or stored.

Further, for example, an ICH, such as ICH 130 of FIG. 1, may be used forensuring that such data is properly passed between the system memory1308 and its appropriate corresponding computing system interface (andinternal storage device if the computing system is so designed) and mayhave bi-directional point-to-point links between itself and the observed110 sources/devices 1304. Similarly, an MCH, such as MCH 116 of FIG. 1,may be used for managing the various contending requests for systemmemory 1308 accesses amongst CPU 1312 and GPU 1314, interfaces andinternal storage elements that may proximately arise in time withrespect to one another.

I/O sources 1304 may include one or more I/O devices that areimplemented for transferring data to and/or from computing device 1300(e.g., a networking adapter); or, for a large scale non-volatile storagewithin computing device 1300 (e.g., hard disk drive). User input device,including alphanumeric and other keys, may be used to communicateinformation and command selections to GPU 1314. Another type of userinput device is cursor control, such as a mouse, a trackball, atouchscreen, a touchpad, or cursor direction keys to communicatedirection information and command selections to GPU 1314 and to controlcursor movement on the display device. Camera and microphone arrays ofcomputer device 1300 may be employed to observe gestures, record audioand video and to receive and transmit visual and audio commands.

Computing device 1300 may further include network interface(s) toprovide access to a network, such as a LAN, a wide area network (WAN), ametropolitan area network (MAN), a personal area network (PAN),Bluetooth, a cloud network, a mobile network (e.g., 3^(rd) Generation(3G), etc.), an intranet, the Internet, etc. Network interface(s) mayinclude, for example, a wireless network interface having antenna, whichmay represent one or more antenna(e). Network interface(s) may alsoinclude, for example, a wired network interface to communicate withremote devices via network cable, which may be, for example, an Ethernetcable, a coaxial cable, a fiber optic cable, a serial cable, or aparallel cable.

Network interface(s) may provide access to a LAN, for example, byconforming to IEEE 802.11b and/or IEEE 802.11g standards, and/or thewireless network interface may provide access to a personal areanetwork, for example, by conforming to Bluetooth standards. Otherwireless network interfaces and/or protocols, including previous andsubsequent versions of the standards, may also be supported. In additionto, or instead of, communication via the wireless LAN standards, networkinterface(s) may provide wireless communication using, for example, TimeDivision, Multiple Access (TDMA) protocols, Global Systems for MobileCommunications (GSM) protocols, Code Division, Multiple Access (CDMA)protocols, and/or any other type of wireless communications protocols.

Network interface(s) may include one or more communication interfaces,such as a modem, a network interface card, or other well-known interfacedevices, such as those used for coupling to the Ethernet, token ring, orother types of physical wired or wireless attachments for purposes ofproviding a communication link to support a LAN or a WAN, for example.In this manner, the computer system may also be coupled to a number ofperipheral devices, clients, control surfaces, consoles, or servers viaa conventional network infrastructure, including an Intranet or theInternet, for example.

It is to be appreciated that a lesser or more equipped system than theexample described above may be preferred for certain implementations.Therefore, the configuration of computing device 1300 may vary fromimplementation to implementation depending upon numerous factors, suchas price constraints, performance requirements, technologicalimprovements, or other circumstances. Examples of the electronic deviceor computer system 1300 may include (without limitation) a mobiledevice, a personal digital assistant, a mobile computing device, asmartphone, a cellular telephone, a handset, a one-way pager, a two-waypager, a messaging device, a computer, a personal computer (PC), adesktop computer, a laptop computer, a notebook computer, a handheldcomputer, a tablet computer, a server, a server array or server farm, aweb server, a network server, an Internet server, a work station, amini-computer, a main frame computer, a supercomputer, a networkappliance, a web appliance, a distributed computing system,multiprocessor systems, processor-based systems, consumer electronics,programmable consumer electronics, television, digital television, settop box, wireless access point, base station, subscriber station, mobilesubscriber center, radio network controller, router, hub, gateway,bridge, switch, machine, or combinations thereof.

Embodiments may be implemented as any or a combination of: one or moremicrochips or integrated circuits interconnected using a parentboard,hardwired logic, software stored by a memory device and executed by amicroprocessor, firmware, an application specific integrated circuit(ASIC), and/or a field programmable gate array (FPGA). The term “logic”may include, by way of example, software or hardware and/or combinationsof software and hardware.

Embodiments may be provided, for example, as a computer program productwhich may include one or more machine-readable media having storedthereon machine-executable instructions that, when executed by one ormore machines such as a computer, network of computers, or otherelectronic devices, may result in the one or more machines carrying outoperations in accordance with embodiments described herein. Amachine-readable medium may include, but is not limited to, floppydiskettes, optical disks, CD-ROMs (Compact Disc-Read Only Memories), andmagneto-optical disks, ROMs, RAMs, EPROMs (Erasable Programmable ReadOnly Memories), EEPROMs (Electrically Erasable Programmable Read OnlyMemories), magnetic or optical cards, flash memory, or other type ofmedia/machine-readable medium suitable for storing machine-executableinstructions.

Moreover, embodiments may be downloaded as a computer program product,wherein the program may be transferred from a remote computer (e.g., aserver) to a requesting computer (e.g., a client) by way of one or moredata signals embodied in and/or modulated by a carrier wave or otherpropagation medium via a communication link (e.g., a modem and/ornetwork connection).

FIG. 14 illustrates a real-time selective data compression mechanism1310 according to one embodiment. In one embodiment, compressionmechanism 1310 may include any number and type of components to performvarious tasks relating to intelligent, dynamic, and real-timecompression of selective data based on real-time information relating tothe user of computing device 1300 and/or the environment surroundingcomputing device 1300. For example and in one embodiment, compressionmechanism 1310 may include any number and type of components, such as(without limitation): reception/detection logic 1401; real-time dataevaluation engine (“evaluation engine”) 1403 including user dataevaluation logic (“user logic”) 1405 and environment data evaluationlogic (“environment logic”) 1407; data selection logic (“selectionlogic”) 1409; compression execution logic (“execution logic”) 1411;rendering logic 1413; and communication/compatibility logic 1415.

As an initial matter, it is contemplated and to be noted that, in oneembodiment, compression mechanism 1310 may be hosted by graphics driverlogic, such as driver logic 1316, of a GPU, such as GPU 1314, of FIG.13, while, in another embodiment, compression mechanism 1310 may not behosted by a GPU and that it may be hosted by an operating system, suchas operating system 1306 of FIG. 13. Similarly, in yet anotherembodiment, various functionalities and/or components of compressionmechanism 1310 may be provided as one or more hardware components ofcomputing device 1300.

It is contemplated that reduction of data traffic is pivotal in savingpower and increasing performance in computing devices, where caching andcompressing are considered two manners for achieving this reduction intraffic. This reduction of data traffic is particularly critical whencomputing device 1300 is based on a mobile platform, such as a tabletcomputer, a smartphone, a wearable device, a head-mounted display, alaptop, etc. In one embodiment, an intelligent real-time compressiontechnique is provided to exploiting a more aggressive lossy compressionbased on the real-time knowledge of the user's behavior and activitiesalong with the ambient characteristics and changes surrounding computingdevice 1300.

For example, users are known to use their mobile devices (e.g.,head-mounted devices, smartphones, etc.) in a variety of environments,such as bright outdoors in the sunlight, dark indoors under lowartificial lights, etc. Further, users are known to change varioussettings, such as brightness levels, color shades, intensity levels,etc., on their mobile devices to save battery life, etc. Another factorto be considered is the distance between a user and a display screen,such as how close the user is to the display screen which may determinehow much of the details or what level of resolution of the displaycontents may be necessary to be displayed to the user without obviouslysacrificing the quality of display contents and/or compromising theuser's viewing experience. In one embodiment, these and other similaruser behaviors, activities, environmental changes, etc., may be takeninto consideration to determine just the right amount of datacompression to reduce the unnecessary data bits from being rendered aspart of the display contents so that efficient rendering may be achievedto reduce power, increase performance, and/or the like.

With the rise in the number of mobile computers and high-resolutiondisplays (e.g., 4K, 5K, etc.) along with the development and increasinguse of high-dynamic range (HDR) displays, embodiments provide for anovel compression technique to maximize the exploitation of real-timeuser activities along with surrounding environmental characteristics toachieve a smart and balanced lossy compression which, in turn, reducesthe burden and pressure on memory systems. For example, considering theperpetual characteristics of a human visual system (HVS), in oneembodiment, a significant decrease in memory traffic may be achieved atcomputing device 1300 without incurring or inferring any visible losses.

It is contemplated and to be noted that embodiments are not limited toany particular type or amount of sensory data or collection of sensorydata based on any particular characteristics or activities of the useror any defined changes to or features of the surrounding environment andaccordingly, any number and type of human and/or environmental factors,features, and functionalities may be taken into consideration whetherthey be natural, non-natural, real, fake, temporary, permanent, and/orthe like. For example, such considerations may range frombrightness/dullness of ambient light, properties/colors of light,expected or existing occultation of portions of display contents (suchas a portion overshadowed by a physical object or the user's own finger,hand, etc.), properties/functionalities of the human eye, humannature/psychology relating to viewing display contents, types ofcontents (e.g., images, graphics, animation, videos, etc.), limitationsof display devices, features of display screens/surfaces,weaknesses/strengths of a GPU/CPU, properties of an overall system ofcomputing device 1300, and/or the like. However, for the sake ofbrevity, clarity, and ease of understanding, only particular examplesare discussed throughout this document but that it is to be noted thatembodiments are not limited as such.

In one embodiment, real-time sensory input data, such as input signalssensed by one or more of capturing/sensing components 1421, relating tothe user and/or the environment associated with the user and/orcomputing device 1300 may be obtained, via reception/detection logic1401, and used to support the graphics processing at the GPU, such asGPU 1314 of FIG. 13, to facilitate data compression at such a level thatalthough the compression may be lossy, the loss may not be visible orapparent to the viewing user. In one embodiment, this may be achieved byany combination of reception, detection, collection, monitoring,interpretation, evaluation, selection, and overall exploitation ofreal-time sensory input data as facilitated by compression mechanism1310 and discussed throughout this document.

Computing device 1300 further includes other components that remain incommunication with compression mechanism 1310, where such othercomponents may include (without limitation): I/O source(s) 1304 havingone or more capturing/sensing components 1421 (e.g., two-dimensional(2D) cameras, three-dimensional (3D) cameras, depth sensing cameras,camera sensors, Red Green Blue (RGB) sensors, etc.), one or more outputcomponents 1423 (e.g., display screens, display devices, display areas,telepresence display areas, telepresence projectors, telepresencemicro-projectors, etc.), and/or the like. Similarly, I/O sources 1304may further include any number and type of other devices, such asoptical imaging plates (e.g., Asukanet plate, etc.), power sources,peripheral devices (e.g., keyboard, mouse), etc.

Computing device 1300 may be in communication with one or morerepositories or databases to store and maintain any amount and type ofdata (e.g., real-time sensory input data, historical contents, metadata,resources, policies, criteria, rules and regulations, upgrades, etc.).Similarly, as aforementioned, computing device 1300 may be incommunication with any number and type of other computing devices over acommunication medium, such as one or more networks including (withoutlimitation) Cloud network, the Internet, intranet, Internet of Things(“IoT”), proximity network, and Bluetooth, etc. It is contemplated thatembodiments are not limited to any particular number or type ofcommunication medium or networks.

Capturing/sensing components 1421 may include any number and type ofcapturing/sensing devices, such as (without limitation) 3D cameras,depth sensing cameras, camera sensors, RGB sensors, microphones,vibration components, tactile components, conductance elements,biometric sensors, chemical detectors, signal detectors,electroencephalography, functional near-infrared spectroscopy, wavedetectors, force sensors (e.g., accelerometers), illuminators, etc.,that may be used for capturing any amount and type of visual data, suchas images (e.g., photos, videos, movies, audio/video streams, etc.), andnon-visual data, such as audio streams (e.g., sound, noise, vibration,ultrasound, etc.), radio waves (e.g., wireless signals, such as wirelesssignals having data, metadata, signs, etc.), chemical changes orproperties (e.g., humidity, body temperature, etc.), biometric readings(e.g., figure prints, etc.), brainwaves, brain circulation,environmental/weather conditions, maps, etc. It is contemplated that“sensor”, “detector”, “capturer” and any variation thereof, such as“sensing”, “detecting”, “capturing”, respectively, may be referencedinterchangeably throughout this document. It is further contemplatedthat one or more capturing/sensing components 1421 may further includeone or more supporting or supplemental devices for capturing and/orsensing of data, such as illuminators (e.g., infrared (IR) illuminator),light fixtures, generators, sound blockers, etc.

It is further contemplated that in one embodiment, capturing/sensingcomponents 1421 may further include any number and type of sensingdevices or sensors (e.g., linear accelerometer) for sensing or detectingany number and type of contexts (e.g., estimating horizon, linearacceleration, etc., relating to a mobile computing device, etc.). Forexample, capturing/sensing components 1421 may include any number andtype of sensors, such as (without limitations): camera sensors; RGBsensors; accelerometers (e.g., linear accelerometer to measure linearacceleration, etc.); inertial devices (e.g., inertial accelerometers,inertial gyroscopes, micro-electro-mechanical systems (MEMS) gyroscopes,inertial navigators, etc.); and gravity gradiometers to study andmeasure variations in gravitation acceleration due to gravity, etc. Forexample, camera sensors and/or RGB sensors may be used to capturereal-time ambient color in the light found in various environments(e.g., indoors, outdoors, etc.) surrounding computing device 1300.

Further, capturing/sensing components 1421 may include (withoutlimitations): audio/visual devices (e.g., cameras, depth sensingcameras, sensors/detectors, microphones, etc.); context-aware sensors(e.g., temperature sensors, facial expression and feature measurementsensors working with one or more cameras of audio/visual devices,environment sensors (such as to sense background colors, lights, etc.),biometric sensors (such as to detect fingerprints, etc.), calendarmaintenance and reading device), etc.; global positioning system (GPS)sensors; resource requestor; and trusted execution environment (TEE)logic. TEE logic may be employed separately or be part of resourcerequestor and/or an I/O subsystem, etc. Capturing/sensing components1421 may further include voice recognition devices, photo recognitiondevices, facial and other body recognition components, voice-to-textconversion components, etc.

Computing device 1300 may further include one or more output components1423 in communication with one or more capturing/sensing components 1421and one or more components of compression mechanism 1310 for detecting,in real-time, environmental ambient color in light and applying that tofacilitate adaption and compensation of colors in contents that arepresented as display outputs. For example, output components 1423 mayinclude one or more display or telepresence projectors to project arealistic and true 3D virtual image that is capable of floating in theair and while having the depth of a real-life image. Further, outputcomponents 1423 may include tactile effectors as an example ofpresenting visualization of touch, where an embodiment of such may beultrasonic generators that can send signals in space which, whenreaching, for example, human fingers can cause tactile sensation or likefeeling on the fingers.

Further, for example and in one embodiment, output components 1423 mayinclude (without limitation) one or more of light sources, displaydevices (e.g., 2D displays, 3D displays, etc.), display screens, displaysurfaces, audio speakers, tactile components, conductance elements, boneconducting speakers, olfactory or smell visual and/or non/visualpresentation devices, haptic or touch visual and/or non-visualpresentation devices, animation display devices, biometric displaydevices, X-ray display devices, high-resolution displays, high-dynamicrange displays, multi-view displays, and head-mounted displays (HMDs)for at least one of virtual reality (VR) and augmented reality (AR),etc.

It is contemplated that a user may put computing device 1300 (e.g.,smartphone, tablet computer, etc.) through any number and type ofenvironments, exposing computing device 1300 to the correspondingconditions and changes, such as varying lights and the colors embeddedin them. For example, when playing outdoors, the user may have computingdevice 1300 under direct sunlight projecting warm (lower ° K, where K isKelvin, the unit of absolute temperature) and predominantly red/yellowenvironmental lights, or when playing indoors under direct neon or CFLbulb projecting cool (higher ° K) and predominantly blue environmentallights. In other words, a cool light having cooler colors (e.g., blue,white, etc.) may have color temperatures of 5,000K or more, while a warmlight having warmer colors (e.g., yellow, orange, red, etc.) may recordcolor temperatures of 3,000K or less.

In one embodiment, lossy compression of selective data may be performedbased on sensory input data including environment light colortemperatures and other context data detected by and received from one ormore sensors, such as camera sensors, RGB sensors, etc., ofcapturing/sensing components 1421, where such parameters may be receivedor detected by reception/detection logic 1401. In one embodiment,sensory input data may include environmental/ambient light-relatedcolors, color temperatures, intensity levels, etc. For example, a camerasensor may be used to capture the environmental color temperatures at ornear the display device and similarly, an RGB sensor may be used toobtain the environmental light level of each RGB component within thelight.

Embodiments are not limited to any particular type or amount of sensorydata and that reception/detection logic 1401 may be used with any numberand type of capturing/sensing components 1421 to sense, detect, and/orreceive one or more of (without limitation): 1) sensing intensity levelsof displays; 2) estimating intensity levels of the ambient light in theenvironment surrounding the user and/or computing device 1300; 3) colorspace input settings of display contents and/or display devices; 4)detecting and navigating a precise point or an area on display screenwhere the user is looking, such as gaze tracking, etc.; 5) sensing alocation of the user or, more precisely, the user's eyes, such as headtracking, etc.; 6) sensing touch on or proximity to the display device;and 7) capturing camera views, such as background views, for augmentedreality applications, etc.

It is contemplated that not all viewing environments may be controlled(such as a theater, a laboratory, an office, a bedroom, etc.) and thus,given most environments surrounding the user and/or computing device1300 are uncontrolled and/or unpredictable, a viewing environment (e.g.,outdoor, indoor, sunny, cloudy, display settings, display screensize/quality, background views, user/device movement, distance betweenthe user and the display screen, etc.) may affect how the human visualsystem may interpret an image being displayed on a display screen/deviceof output components 1423. For example, since contemporary displaydevices greatly vary in quality and performance and their mobilityallows for flexibility in their use, ranging from bright outdoors todark indoors, if the light intensity of a mobile display is lowered(such as to save battery life) or too much background light is detected(such as due to the sunlight), then, in one embodiment, this viewingenvironment status may be detected and monitored using one or moresensors of capturing/sensing components 1421 (e.g., RGB sensors) andreception/detection logic 1401 to quantize the colors and achieve abetter compression of data for more efficient rendering of contents fordisplay.

It is to be noted that embodiments are not merely limited to ambientlights; however, for the sake of brevity, clarity, and ease ofunderstanding, continuing with this light example, lights and theircolors may vary, from slightly to profoundly, each time computing device1300 changes its one or more of its surrounding (e.g., lights turnedoff/on, from sunny to cloudy, etc.), location (e.g., from indoors tooutdoors), local placement (e.g., moved from table to chair),orientation (e.g., from portrait to landscape or corresponding to minoruser movements), and power supply (e.g., battery going from high to lowor vice versa), and/or the like. In one embodiment, such changes may besensed, monitored, and obtained as sensory data using one or moresensors of capturing/sensing logic 1421, as facilitated byreception/detection logic 1401, where this user/environmental sensorydata may then be used to continuously perform the lossy compression ofselected data at various rendering stages while continuously renderingthe remaining contents for the user to view at a display screen ofoutput components 1423 of computing device 1300.

In one embodiment, reception/detection logic 1401 may be used forreal-time detection of various characteristics of the human visualsystem which may then be exploited by other components of compressionmechanism 1310 to achieve dynamic lossy image and/or video compression.In one embodiment, any sensory data may be detected and obtaineddynamically and in real-time because continuing changes to useractivities (e.g., sitting on a chair, standing in a train, leaving aroom, eye/head movement, changing distance between the user andcomputing device 1300, etc.) and environmental characteristics (e.g.,brightness/darkness of light, outdoors/indoors, changingbackground/foreground, power limitations (e.g., battery life), displayscreen quality/capability, etc.) are to be expected and captured inreal-time.

For example and in one embodiment, data compression may be performedbased on real-time data relating to the user and/or the user's viewingenvironment which may be applied to any number and type of real-timerendering and displaying of contents at computing device 1300, where therendering may range from simple desktop compositing scenario to complex3D gaming and AR scenarios.

Once the sensory input data relating to the user and/or the user'sviewing/surrounding environment is detected by or received atreception/detection logic 1401, this sensory input data may then beevaluated by various components of sensory data evaluation engine 1403for further processing. For example, any sensory input data relating tothe user of computing device 1300 may be evaluated by user dataevaluation logic 1405, while any sensory input data relating to theviewing environment relating to the user and/or surround computingdevice 1300 may be evaluated by environment data evaluation logic 1407.In one embodiment, user-related sensory input data may include (withoutlimitation) gaze/eye tracking, head tracking, position/location of theuser with respect to the display device of output components 1423, etc.In one embodiment, viewing environment-related sensory input data mayinclude (without limitation) color/light data relating to the ambientlight in the environment (e.g., indoor light, outdoor light, brightness,darkness, etc.), background views, VR, AR, display device intensitylevels, types of display contents, etc.

It is contemplated that modern display devices of output components 1423are available in many different sizes and varieties, such as (withoutlimitation) HMDs for VR and/or AR, high-resolution displays, multi-viewdisplays, and/or the like, and thus, in one embodiment, detectingreal-time sensory data relating to head tracking, gaze tracking, ambientlighting, etc., may be used to dynamically perform lossy compression ofdata to facilitate high-quality and low-power rendering of contents onsuch a display screen without being noticeable or apparent of the lossof data to the user of computing device 1300.

In one embodiment, evaluation engine 1403 evaluates the user and/orenvironment sensory input data to determine the most efficient manner inwhich to compress the data, such as which portion of the data tocompress out without ruining the user's viewing experience. For example,as illustrated with respect to FIG. 15, if the user is focused at thecore of an image, performing lossy compression on the data in theperipheral portions of the image may not matter as much to the user asthe user is not expected to notice the peripheral part of the imageanyways. In one embodiment, any evaluation results formed by evaluationengine 1403 may indicate the data (e.g., pixels, specific portions,specific location, etc., of data) that is determined to becompression-suitable and marked as such to be selected for compression,where the evaluation results are communicated from evaluation engine1403 to data selection logic 1409 for further processing. Further, asaforementioned, in one embodiment, eye or gaze tracking may be used totrack the user's gaze, such as where the user is looking, and thecompress operation is done with higher loss in chroma, etc., the fartheraway from the point where the user is looking.

In one embodiment, evaluation engine 1403 may take any number and typeof factors, features, behaviors, natural laws, principles, formulae,etc., into consideration when evaluating the sensory input data. Asaforementioned, such consideration may range anywhere from general humannature and particular user behavior to environmental characteristics andambient features to background landscapes and changing weather to systemlimitations and content types, and/or the like.

With regard to known principles or laws, for example, evaluation engine1403 may take into consideration Weber's law (also known as“Weber-Fechner law”) to be used to evaluate the sensory data collectedin previous frames to guide the quantization and lossy compression.Weber's law, which deals with psychophysics of human perception, statesthat a change in a stimulus that is barely noticeable is a constantratio of the original stimulus (within limits). For example, incomparing the current color of a pixel or tile with that of a previousframe, or a weighted average of a last M frame, how much the stimulus(e.g., intensity, color, etc.) has changed may be detected. This, forexample, may be used by evaluation engine 1403 to determine anappropriate level of quantization which, in turn, indicates the amountand type of data that may be compressed without making the loss of datanoticeable to the user. This data is marked by evaluation engine 1403 ascompression-worthy and sent as evaluation results to selection logic1409 for further processing. It is contemplated that any color datarelating to the previous frame(s) may be available in and obtained froma typical 3D workloads as it is often used for other purposes, such asre-projection in game engines, double buffering for displaysynchronization, and/or the like.

Once evaluation results are received at selection logic 1409, the markeddata from the evaluation results is detected and selected, in real-time,for lossy compression by selection logic 1409. It is to be noted thatthis marking and selecting of compression-candidate data is performedbased on real-time sensory input data and thus, this novel real-timelossy compression technique is distinguished from one-time compressiontechniques where the data to be compressed is predetermined even if theuser and/or environmental conditions change and no longer support thepredetermination of the data for compression. Embodiments provide forlossy buffer compression of data, where the data may be generated,re-compressed, and/or consumed multiple times, etc., as opposed to theone-time compression and consumption as used for video and textures.

In one embodiment, upon selecting the marked data for compression asfacilitated by selection logic 1409, compression execution logic 1411may then be triggered to perform the lossy compression of the selecteddata. Further, in one embodiment, execution logic 1411 may work withrendering logic 1413 to ensure that upon compression of the selecteddata, the rest of the data is continuously rendered. In one embodiment,the compression of selected data by execution logic 1411 and renderingof the rest of the data for content displaying may be performed atvarious stages of rendering and as an input to auxiliary functions, suchas compression. In another embodiment, any amount of sensory input datamay be known by the rendering pipeline. Additional processes relating tocompression and rendering as facilitated by execution logic 1411 andrendering logic 1413, respectively, are illustrated with respect toFIGS. 16A-16B.

For example and in one embodiment, capturing/sensing components 1421 mayinclude one or more tracking components for eye tracking, head tracking,etc., as facilitated by detection/reception logic 1401, to track anddetermine one or more user-related awareness characteristics oractivities, such as the user's distance from or location relative to adisplay device associated with computing device 1300. This sensory datarevealing the user's distance/location relating to the display devicemay then be evaluated by user logic 1405 of evaluation engine 1403 tofurther determine the user's distance in relation to the pixel densityof display contents to evaluate an appropriate level of compression. Forexample, if the user is sufficiently far from the display device ofoutput components 1423 computing device 1300, the user's natural abilityto evaluate and discern differences between neighboring pixels may bereduced. Similarly, the angle of the display device's surface relativeto the user may also be used as sensory data which may then be evaluatedby evaluation engine 1403 to determine whether to, locally or globally,increase the level of compression.

Further, one or more gazing or eye tracking components ofcapturing/sensing components 1421 may be used to detect various grazingangles relating to the movement of the user's eyes with respect to thedisplay screen, where these grazing angles may be used, locally orglobally, to change, such as increase, the level of compression. Forexample, at grazing angles, pixels may appear more tightly packed,making it harder for the user to notice any differences (such as in caseof non-flat display surfaces) which may be well-suited for performinglossy compression as facilitated by execution logic 1411 and renderinglogic 1413.

Similarly, for example and in one embodiment, one or more touch and/orproximity sensors of capturing/sensing components 1421 as provided onthe display surface of a display device may be used for collectingsensory data relating to the user's touching of the display surface,such as in case of a display surface being a touch screen, etc., tospatially guide the application of compression and/or quantization. Forexample, any tiles on a display screen that overlap with one or morelocations on the screen that the user's fingers (e.g., finger tips)touch (e.g., tap) may be heavily compressed or simply removed from beingrendered in the final image.

As with detecting the user's touch, for example, one or more touchand/or proximity sensors may be used by reception/detection logic 1401to detect the proximity or nearness of the user's fingers, palm, hand,etc., from the display screen before and/or after the user's touching ofthe screen. Further, in one embodiment, any sensory data collected viaone or more touch and/or proximity sensors may be used with additionalsensory data collected by one or more of other capturing/sensingcomponents 1421, such as a head/eye tracking component, to be used byevaluation engine 1403 for determining the marked data which may then beselected by selection logic 1409 and compressed by execution logic 1411for efficient rendering of the final data as facilitated by renderinglogic 1413 based on a combination of the aforementioned real-timetouch/proximity/tracking sensory data, such as by reducing the qualityof display contents in regions that are likely to be occluded (e.g.,covered, hidden, etc.) by the user's finger(s), hand, etc., whentouching the display screen.

Upon execution of compression of the selected data (where thiscompression may be continuous and performed, in real-time, at variousrendering stages) by execution logic 1411, the remaining data continuousto be rendered, in real-time, by rendering logic 1413 and provided asdisplay contents to the display device where the display contents aredisplayed absent the compressed data without having the user noticingthe missing data when viewing the display contents.

Communication/compatibility logic 1415 may be used to facilitate dynamiccommunication and compatibility between one or more computing devices,such as computing device 1300 of FIG. 13, and any number and type ofother computing devices (such as mobile computing device, desktopcomputer, server computing device, etc.), processing devices (such asCPUs, GPUs, etc.), capturing/sensing/detecting devices (such ascapturing/sensing components 1421 including cameras, depth sensingcameras, camera sensors, RGB sensors, microphones, etc.), displaydevices (such as output components 1423 including display screens,display areas, display projectors, etc.), user/context-awarenesscomponents and/or identification/verification sensors/devices (such asbiometric sensors/detectors, scanners, etc.), memory or storage devices,databases, and/or data sources (such as data storage devices, harddrives, solid-state drives, hard disks, memory cards or devices, memorycircuits, etc.), communication channels or networks (e.g., Cloudnetwork, the Internet, intranet, cellular network, proximity networks,such as Bluetooth, Bluetooth low energy (BLE), Bluetooth Smart, Wi-Fiproximity, Radio Frequency Identification (RFID), Near FieldCommunication (NFC), Body Area Network (BAN), etc.), wireless or wiredcommunications and relevant protocols (e.g., Wi-Fi®, WiMAX, Ethernet,etc.), connectivity and location management techniques, softwareapplications/websites, (e.g., social and/or business networkingwebsites, etc., business applications, games and other entertainmentapplications, etc.), programming languages, etc., while ensuringcompatibility with changing technologies, parameters, protocols,standards, etc.

Throughout this document, terms like “logic”, “component”, “module”,“framework”, “engine”, and the like, may be referenced interchangeablyand include, by way of example, software, hardware, and/or anycombination of software and hardware, such as firmware. Further, any useof a particular brand, word, term, phrase, name, and/or acronym, such as“GPU”, “GPU domain”, “CPU”, “CPU domain”, “environmental”, “sensorydata” or “sensory input data”, “compression” or “lossy compression”,“lossy”, “Weber's Law”, etc., should not be read to limit embodiments tosoftware or devices that carry that label in products or in literatureexternal to this document.

It is contemplated that any number and type of components may be addedto and/or removed from compression mechanism 1310 to facilitate variousembodiments including adding, removing, and/or enhancing certainfeatures. For brevity, clarity, and ease of understanding of compressionmechanism 1310, many of the standard and/or known components, such asthose of a computing device, are not shown or discussed here. It iscontemplated that embodiments, as described herein, are not limited toany particular technology, topology, system, architecture, and/orstandard and are dynamic enough to adopt and adapt to any futurechanges.

FIG. 15 illustrates a visual field 1500 in consideration for real-timeand dynamic lossy compression of data according to one embodiment. As aninitial matter, for brevity, clarity, and ease of understanding, many ofthe details previously discussed with reference to FIGS. 1-14 may not berepeated or discussed hereafter.

As aforementioned, embodiments are not limited to any particular typesor amounts of user and/or environmental features, factors,functionalities, properties, behavior, considerations, etc. andaccordingly, this illustration is provided as an example for the sake ofbrevity, clarity, and ease of understanding.

For example, in relation to various properties of HVS, humans are notknown to perceive any difference between two different light intensitiesthat differ by less than 1%. For example, in a typical indoorenvironment (such as home, office), an effective contrast ratio of mostdisplay devices may be in the vicinity of 100:1, such as correspondingto 463 discernable levels of intensity, 8.85 bits of precision, etc. Forexample, a typical display device may have about 8 bits precision, percomponent, and 257 levels of intensity, resulting in barely noticeableintensity level granularity of 1.8%. Now, when using the same displaydevice outdoors, the effect contrast ratio may experience a significantdrop due to dark colors reflecting more light from the environment. Forexample, at an effective contrast ratio of 10:1, the same 1.8% intensitylevel granularity may correspond to merely 128 discernable levels ofintensity, requiring merely 7 bits of precision. Accordingly, in someembodiments, fewer bits of precision may be preserved in cases wheremeasured effective contrast is determined to be low and if, on the otherhand, the user is in a dark room where even small differences are easilynoticeable, any lossy compression of data may be automatically turnedoff.

It is contemplated that various cones in the retina of a human eye mayhave diminishing efficiency at very low light intensities such that ifthe environment is very dark, only the rods may provide significantinformation in the eye, causing degradation or even loss of colorperception in the dark. This may also be used to compress chromaticinformation to a very high degree when the display brightness is turneddown, such as in case of a wearable device worn at night, an in-vehiclenavigational system, etc. Accordingly, in some embodiments, a lesseramount of chrome precision may be preserved in cases where theambient/environmental and display light intensities are low.

As illustrated here with respect to visual field 1500, human colorperception with regard to chromas 1501-1507 fall off rapidly towards theperiphery of visual field 1500 and therefore difference between thecolors in the periphery, such as nearing the cones of lowest chroma1507, low chroma 1505, etc., may not be discerned and merely itsluminance may be seen. For example, for visual or augmented realityheadsets having gaze tracking, etc., chromatic information may begreatly compressed in the periphery, such as nearing lowest chroma 1507,low chroma 1505, etc., as opposed to the core, such as nearing highestchroma 1501, high chroma 1503, etc., of the user's field of vision 1500.For the reasons set forth above, although this heavy compression mayresult in a loss of significant portions of data, but this loss may notbe detected by or noticeable to the user viewing the resulting displaycontent on a display device as facilitated by compression mechanism 1310of FIGS. 13-14.

It is contemplated that schematically, any chroma information relatingto chromas 1501-1507 may be needed to present a perpetually equivalentimage to be viewed by the user as illustrated here as visual field 1500,where the amount of chroma information is matched against HVS. Further,to some extent, this same reasoning may apply to luminance informationwhich may therefore be more heavily compressed or quantized in theperiphery without any noticeable or apparent loss of data. For exampleand in one embodiment, the most significant bits, N, of each colorcomponents may be kept, while, in another embodiment, an amount ofquantization applied to each color component may be determined based onone or more of 1) spatial location of a tile on the display screen, 2)absolute intensity levels of the display screen and the surroundingenvironment, 3) values of the color components for non-linearquantization, 4) chrominance/luminance response curve of the human eye,5) data collected from previous frames, and 6) any combination thereof.

In one embodiment, one technique for leveraging input signals may be toapply color pre-processing before applying an existing color compressionscheme. For example, a function (per component) derived from all inputsignals may be used to quantize individual color components, such as(without limitation): red′=f_(r)(red), green′=f_(g)(green),blue′=f_(b)(blue), and alpha′=f_(a)(alpha), where the input colors tocompress are red′, green′, blue′, and alpha′, respectively. Any suchquantization lowers the entropy in the color information whileincreasing the chances of successful compression using any lossy orlossless codec. Quantization may occur either at the time of datageneration (such as during pixel shading) or when storing the data (suchas when writing the rendered cache) or at eviction from the renderedcache prior to compression, etc.

FIG. 16A illustrates a method 1600 for collection and use of sensoryinput data at various rendering stages according to one embodiment.Method 1600 may be performed by processing logic that may comprisehardware (e.g., circuitry, dedicated logic, programmable logic, etc.),software (such as instructions run on a processing device), or acombination thereof. In one embodiment, method 1600 may be performed bycompression mechanism 1310 of FIGS. 13-14. The processes of method 1600are illustrated in linear sequences for brevity and clarity inpresentation; however, it is contemplated that any number of them can beperformed in parallel, asynchronously, or in different orders. Forbrevity, many of the details discussed with reference to the precedingFIGS. 1-15 may not be discussed or repeated hereafter.

In one embodiment, sensory input data 1605 may be collected in real timeand used in various stages of rendering and as input to auxiliaryfunctions, such as compression as facilitated by compression mechanism1310 of FIGS. 13-14. In some embodiments, sensory input data 1605 may beknown by the rendering pipeline. Method 1600 starts at block 1601 andcontinues with collection of sensory input data at block 1603, where, asaforementioned, sensory input data 1605 may include information relatingto display intensity levels, ambient light, color space input settings,user/viewer gaze points, user/viewer head locations, etc.

As illustrated, sensory input data 1605 may be used and applied atvarious rendering stages, such as at rendering before pixel shading atblock 1607 or at a subsequent rendering stage of pixel shading of tilesof pixels at block 1609. At block 1611, a decision is made as to whetherany pixels/samples are left to shade. If yes, method 1600 continues withpixel shading of tiles of pixels at block 1609. If not, method 1600continues with the rest of rending at block 1613. Further, in oneembodiment, sensory input data 1605 may be used and applied at thisstage of the rest of rendering at block 1613 and upon performing therest of rendering at block 1613, method 1600 ends at block 1615.

FIG. 16B illustrates a method 1650 for tile-based color compressionaccording to one embodiment. Method 1650 may be performed by processinglogic that may comprise hardware (e.g., circuitry, dedicated logic,programmable logic, etc.), software (such as instructions run on aprocessing device), or a combination thereof. In one embodiment, method1650 may be performed by compression mechanism 1310 of FIGS. 13-14. Theprocesses of method 1650 are illustrated in linear sequences for brevityand clarity in presentation; however, it is contemplated that any numberof them can be performed in parallel, asynchronously, or in differentorders. For brevity, many of the details discussed with reference to thepreceding FIGS. 1-16A may not be discussed or repeated hereafter.

In one embodiment, an encoder may be responsible for compressing thecolor data within a tile, with or without loss, into a fewer number ofbits. Given that the peripheral data can be represented with less colorinformation and less luminance information, the success rate of such acompressor can be greatly improved. Further, any individual color valuesin this case may be of lower entropy and therefore exhibit higherlocality and amenability to compression. As previous described withreference to FIG. 16A, sensory input data 1655 may be used either in therendering process to output reduced amounts of data per pixel or sample,or by the compression process to store less amount of data per pixel orsample. It is contemplated and to be noted, however, that embodimentsare not limited to merely compression of color as discussed throughoutthis document.

Referring now to method 1650, it starts at block 1651 and proceeds withcompression of tile color data at block 1653 using one or more inputs,such as sensory input data 1655 and tile color data 1657, where tilecolor data 1657 may be generated by the GPU, such as GPU 1314 of FIG.13. At block 1659, a determination may be made as to whether acompression ratio has been achieved. In one embodiment, the compressionratio may relate to one or more memory architecture-specific ratios,such as a number of compression bits, cache lines, etc. If thecompression ratio is not achieved, at block 1661, the data remainsuncompressed and is stored as such. If, however, the compression ratiois achieved, at block 1663, the data is compressed and is stored assuch. At block 1665, the compression control surface is updated toindicate, for example, how the data is to be interpreted in memory andsubsequently, the process then ends at block 1667.

FIG. 16C illustrates a method 1680 for real-time and dynamic losscompression of data according to one embodiment. Method 1680 may beperformed by processing logic that may comprise hardware (e.g.,circuitry, dedicated logic, programmable logic, etc.), software (such asinstructions run on a processing device), or a combination thereof. Inone embodiment, method 1680 may be performed by compression mechanism1310 of FIGS. 13-14. The processes of method 1680 are illustrated inlinear sequences for brevity and clarity in presentation; however, it iscontemplated that any number of them can be performed in parallel,asynchronously, or in different orders. For brevity, many of the detailsdiscussed with reference to the preceding FIGS. 1-16B may not bediscussed or repeated hereafter.

Method 1680, in one embodiment, begins at block 1681 with a real-timecollection of user and/or environmental sensory input data, such asthrough reception, detection, and monitoring of user and/orenvironmental characteristics, etc. At block 1683, in one embodiment,the real-time sensory input data may be evaluated to determine and markthe compression-suitable data of the overall data to be displayed to auser. At block 1685, the marked data is selected for compression. Atblock 1687, the selected data is then dynamically, and in real-time,executed, where this compression includes lossy compression such thatthe selected data, per pixel or sample, may be removed or discarded fromthe overall data to be displayed to the user. At block 1689, the rest ofthe overall data is efficiently rendered as display content, via adisplay device, such that the loss of this compressed data may not bevisible or noticeable to the user viewing the display content.

References to “one embodiment”, “an embodiment”, “example embodiment”,“various embodiments”, etc., indicate that the embodiment(s) sodescribed may include particular features, structures, orcharacteristics, but not every embodiment necessarily includes theparticular features, structures, or characteristics. Further, someembodiments may have some, all, or none of the features described forother embodiments.

In the foregoing specification, embodiments have been described withreference to specific exemplary embodiments thereof. It will, however,be evident that various modifications and changes may be made theretowithout departing from the broader spirit and scope of embodiments asset forth in the appended claims. The Specification and drawings are,accordingly, to be regarded in an illustrative rather than a restrictivesense.

In the following description and claims, the term “coupled” along withits derivatives, may be used. “Coupled” is used to indicate that two ormore elements co-operate or interact with each other, but they may ormay not have intervening physical or electrical components between them.

As used in the claims, unless otherwise specified the use of the ordinaladjectives “first”, “second”, “third”, etc., to describe a commonelement, merely indicate that different instances of like elements arebeing referred to, and are not intended to imply that the elements sodescribed must be in a given sequence, either temporally, spatially, inranking, or in any other manner.

The following clauses and/or examples pertain to further embodiments orexamples. Specifics in the examples may be used anywhere in one or moreembodiments. The various features of the different embodiments orexamples may be variously combined with some features included andothers excluded to suit a variety of different applications. Examplesmay include subject matter such as a method, means for performing actsof the method, at least one machine-readable medium includinginstructions that, when performed by a machine cause the machine toperforms acts of the method, or of an apparatus or system forfacilitating hybrid communication according to embodiments and examplesdescribed herein.

Some embodiments pertain to Example 1 that includes an apparatus tofacilitate environment-based lossy compression of data for efficientrendering of contents at computing devices, comprising:reception/detection logic to collect, in real time, sensory input datarelating to characteristics of at least one of a user and a surroundingenvironment; real-time data evaluation engine to evaluate the sensoryinput data to mark one or more data portions of data relating tocontents, wherein the one or more data portions are determined to besuitable for compression based on the sensory input data; compressionexecution logic to dynamically perform, in real time, the compression ofthe one or more data portions, wherein the compression triggers loss ofone or more content portions of the contents corresponding to the one ormore data portions of the data; and rendering logic to render thecontents to be displayed missing the one or more content portions,wherein the missing of the one or more content portions from thecontents is not apparent to the user viewing the contents via a displaydevice.

Example 2 includes the subject matter of Example 1, where the sensoryinput data comprises user sensory data relating to the user, wherein thereal-time data evaluation engine includes user data evaluation logic toevaluate the user sensory data based on one or more usercharacteristics.

Example 3 includes the subject matter of Example 2, wherein the one ormore user characteristics comprise at least one of general humanbehavior, specific user behavior, user activities, user gaze points,user head locations, and user distance from the display device.

Example 4 includes the subject matter of Example 1, where the sensoryinput data comprises environment sensory data relating to thesurrounding environment, wherein the real-time data evaluation engineincludes environment data evaluation logic to evaluate the environmentsensory data based on one or more ambient characteristics.

Example 5 includes the subject matter of Example 4, wherein the one ormore ambient characteristics comprise at least one of ambient lightbrightness levels, ambient light colors, color space input settings,background views, temperature settings, power levels, display deviceintensity levels, display device limitations, and natural laws.

Example 6 includes the subject matter of Example 1, wherein the sensoryinput data is collected using one or more capturing/sensing componentscomprising at least one of a three-dimensional (3D) camera, a depthsensing camera, a camera sensor, a Red Green Blue (RGB) sensor, a gazetracking component, and a head tracking component.

Example 7 includes the subject matter of Example 1, wherein the displaydevice comprises at least one of a high-resolution display, ahigh-dynamic range display, a multi-view display, and a head-mounteddisplay (HMD) for at least one of virtual reality (VR) and augmentedreality (AR).

Some embodiments pertain to Example 8 that includes a method forfacilitating environment-based lossy compression of data for efficientrendering of contents at computing devices, comprising: collecting, inreal time, sensory input data relating to characteristics of at leastone of a user and a surrounding environment; evaluating the sensoryinput data to mark one or more data portions of data relating tocontents, wherein the one or more data portions are determined to besuitable for compression based on the sensory input data; dynamicallyperforming, in real time, the compression of the one or more dataportions, wherein the compression triggers loss of one or more contentportions of the contents corresponding to the one or more data portionsof the data; and rendering the contents to be displayed missing the oneor more content portions, wherein the missing of the one or more contentportions from the contents is not apparent to the user viewing thecontents via a display device.

Example 9 includes the subject matter of Example 8, where the sensoryinput data comprises user sensory data relating to the user, wherein theuser sensory data is evaluated based on one or more usercharacteristics.

Example 10 includes the subject matter of Example 9, wherein the one ormore user characteristics comprise at least one of general humanbehavior, specific user behavior, user activities, user gaze points,user head locations, and user distance from the display device.

Example 11 includes the subject matter of Example 8, where the sensoryinput data comprises environment sensory data relating to thesurrounding environment, wherein the environment sensory data isevaluated based on one or more ambient characteristics.

Example 12 includes the subject matter of Example 11, wherein the one ormore ambient characteristics comprise at least one of ambient lightbrightness levels, ambient light colors, color space input settings,background views, temperature settings, power levels, display deviceintensity levels, display device limitations, and natural laws.

Example 13 includes the subject matter of Example 8, wherein the sensoryinput data is collected using one or more capturing/sensing componentscomprising at least one of a three-dimensional (3D) camera, a depthsensing camera, a camera sensor, a Red Green Blue (RGB) sensor, a gazetracking component, and a head tracking component.

Example 14 includes the subject matter of Example 8, wherein the displaydevice comprises at least one of a high-resolution display, ahigh-dynamic range display, a multi-view display, and a head-mounteddisplay (HMD) for at least one of virtual reality (VR) and augmentedreality (AR).

Example 15 includes at least one machine-readable medium comprising aplurality of instructions, when executed on a computing device, toimplement or perform a method or realize an apparatus as claimed in anypreceding claims.

Example 16 includes at least one non-transitory or tangiblemachine-readable medium comprising a plurality of instructions, whenexecuted on a computing device, to implement or perform a method orrealize an apparatus as claimed in any preceding claims.

Example 17 includes a system comprising a mechanism to implement orperform a method or realize an apparatus as claimed in any precedingclaims.

Example 18 includes an apparatus comprising means to perform a method asclaimed in any preceding claims.

Example 19 includes a computing device arranged to implement or performa method or realize an apparatus as claimed in any preceding claims.

Example 20 includes a communications device arranged to implement orperform a method or realize an apparatus as claimed in any precedingclaims.

Some embodiments pertain to Example 21 includes a system comprising astorage device having instructions, and a processor to execute theinstructions to facilitate a mechanism to perform one or more operationscomprising: collecting, in real time, sensory input data relating tocharacteristics of at least one of a user and a surrounding environment;evaluating the sensory input data to mark one or more data portions ofdata relating to contents, wherein the one or more data portions aredetermined to be suitable for compression based on the sensory inputdata; dynamically performing, in real time, the compression of the oneor more data portions, wherein the compression triggers loss of one ormore content portions of the contents corresponding to the one or moredata portions of the data; and rendering the contents to be displayedmissing the one or more content portions, wherein the missing of the oneor more content portions from the contents is not apparent to the userviewing the contents via a display device.

Example 22 includes the subject matter of Example 21, where the sensoryinput data comprises user sensory data relating to the user, wherein theuser sensory data is evaluated based on one or more usercharacteristics.

Example 23 includes the subject matter of Example 22, wherein the one ormore user characteristics comprise at least one of general humanbehavior, specific user behavior, user activities, user gaze points,user head locations, and user distance from the display device.

Example 24 includes the subject matter of Example 21, where the sensoryinput data comprises environment sensory data relating to thesurrounding environment, wherein the environment sensory data isevaluated based on one or more ambient characteristics.

Example 25 includes the subject matter of Example 24, wherein the one ormore ambient characteristics comprise at least one of ambient lightbrightness levels, ambient light colors, color space input settings,background views, temperature settings, power levels, display deviceintensity levels, display device limitations, and natural laws.

Example 26 includes the subject matter of Example 21, wherein thesensory input data is collected using one or more capturing/sensingcomponents comprising at least one of a three-dimensional (3D) camera, adepth sensing camera, a camera sensor, a Red Green Blue (RGB) sensor, agaze tracking component, and a head tracking component.

Example 27 includes the subject matter of Example 21, wherein thedisplay device comprises at least one of a high-resolution display, ahigh-dynamic range display, a multi-view display, and a head-mounteddisplay (HMD) for at least one of virtual reality (VR) and augmentedreality (AR).

Some embodiments pertain to Example 28 includes an apparatus comprising:means for collecting, in real time, sensory input data relating tocharacteristics of at least one of a user and a surrounding environment;means for evaluating the sensory input data to mark one or more dataportions of data relating to contents, wherein the one or more dataportions are determined to be suitable for compression based on thesensory input data; means for dynamically performing, in real time, thecompression of the one or more data portions, wherein the compressiontriggers loss of one or more content portions of the contentscorresponding to the one or more data portions of the data; and meansfor rendering the contents to be displayed missing the one or morecontent portions, wherein the missing of the one or more contentportions from the contents is not apparent to the user viewing thecontents via a display device.

Example 29 includes the subject matter of Example 28, where the sensoryinput data comprises user sensory data relating to the user, wherein theuser sensory data is evaluated based on one or more usercharacteristics.

Example 30 includes the subject matter of Example 29, wherein the one ormore user characteristics comprise at least one of general humanbehavior, specific user behavior, user activities, user gaze points,user head locations, and user distance from the display device.

Example 31 includes the subject matter of Example 28, where the sensoryinput data comprises environment sensory data relating to thesurrounding environment, wherein the environment sensory data isevaluated based on one or more ambient characteristics.

Example 32 includes the subject matter of Example 31, wherein the one ormore ambient characteristics comprise at least one of ambient lightbrightness levels, ambient light colors, color space input settings,background views, temperature settings, power levels, display deviceintensity levels, display device limitations, and natural laws.

Example 33 includes the subject matter of Example 28, wherein thesensory input data is collected using one or more capturing/sensingcomponents comprising at least one of a three-dimensional (3D) camera, adepth sensing camera, a camera sensor, a Red Green Blue (RGB) sensor, agaze tracking component, and a head tracking component.

Example 34 includes the subject matter of Example 28, wherein thedisplay device comprises at least one of a high-resolution display, ahigh-dynamic range display, a multi-view display, and a head-mounteddisplay (HMD) for at least one of virtual reality (VR) and augmentedreality (AR).

Example 35 includes at least one non-transitory or tangiblemachine-readable medium comprising a plurality of instructions, whenexecuted on a computing device, to implement or perform a method asclaimed in any of claims or examples 8-14.

Example 36 includes at least one machine-readable medium comprising aplurality of instructions, when executed on a computing device, toimplement or perform a method as claimed in any of claims or examples8-14.

Example 37 includes a system comprising a mechanism to implement orperform a method as claimed in any of claims or examples 8-14.

Example 38 includes an apparatus comprising means for performing amethod as claimed in any of claims or examples 8-14.

Example 39 includes a computing device arranged to implement or performa method as claimed in any of claims or examples 8-14.

Example 40 includes a communications device arranged to implement orperform a method as claimed in any of claims or examples 8-14.

The drawings and the forgoing description give examples of embodiments.Those skilled in the art will appreciate that one or more of thedescribed elements may well be combined into a single functionalelement. Alternatively, certain elements may be split into multiplefunctional elements. Elements from one embodiment may be added toanother embodiment. For example, orders of processes described hereinmay be changed and are not limited to the manner described herein.Moreover, the actions any flow diagram need not be implemented in theorder shown; nor do all of the acts necessarily need to be performed.Also, those acts that are not dependent on other acts may be performedin parallel with the other acts. The scope of embodiments is by no meanslimited by these specific examples. Numerous variations, whetherexplicitly given in the specification or not, such as differences instructure, dimension, and use of material, are possible. The scope ofembodiments is at least as broad as given by the following claims.

What is claimed is:
 1. An apparatus comprising: reception/detectionlogic to collect, in real time, sensory input data relating tocharacteristics of at least one of a user and a surrounding environment;real-time data evaluation engine to evaluate the sensory input data tomark one or more data portions of data relating to contents, wherein theone or more data portions are determined to be suitable for compressionbased on the sensory input data; compression execution logic todynamically perform, in real time, the compression of the one or moredata portions, wherein the compression triggers loss of one or morecontent portions of the contents corresponding to the one or more dataportions of the data; and rendering logic to render the contents to bedisplayed missing the one or more content portions, wherein the missingof the one or more content portions from the contents is not apparent tothe user viewing the contents via a display device.
 2. The apparatus ofclaim 1, where the sensory input data comprises user sensory datarelating to the user, wherein the real-time data evaluation engineincludes user data evaluation logic to evaluate the user sensory databased on one or more user characteristics.
 3. The apparatus of claim 2,wherein the one or more user characteristics comprise at least one ofgeneral human behavior, specific user behavior, user activities, usergaze points, user head locations, and user distance from the displaydevice.
 4. The apparatus of claim 1, where the sensory input datacomprises environment sensory data relating to the surroundingenvironment, wherein the real-time data evaluation engine includesenvironment data evaluation logic to evaluate the environment sensorydata based on one or more ambient characteristics.
 5. The apparatus ofclaim 4, wherein the one or more ambient characteristics comprise atleast one of ambient light brightness levels, ambient light colors,color space input settings, background views, temperature settings,power levels, display device intensity levels, display devicelimitations, and natural laws.
 6. The apparatus of claim 1, wherein thesensory input data is collected using one or more capturing/sensingcomponents comprising at least one of a three-dimensional (3D) camera, adepth sensing camera, a camera sensor, a Red Green Blue (RGB) sensor, agaze tracking component, and a head tracking component.
 7. The apparatusof claim 1, wherein the display device comprises at least one of ahigh-resolution display, a high-dynamic range display, a multi-viewdisplay, and a head-mounted display (HMD) for at least one of virtualreality (VR) and augmented reality (AR).
 8. A method comprising:collecting, in real time, sensory input data relating to characteristicsof at least one of a user and a surrounding environment; evaluating thesensory input data to mark one or more data portions of data relating tocontents, wherein the one or more data portions are determined to besuitable for compression based on the sensory input data; dynamicallyperforming, in real time, the compression of the one or more dataportions, wherein the compression triggers loss of one or more contentportions of the contents corresponding to the one or more data portionsof the data; and rendering the contents to be displayed missing the oneor more content portions, wherein the missing of the one or more contentportions from the contents is not apparent to the user viewing thecontents via a display device.
 9. The method of claim 8, where thesensory input data comprises user sensory data relating to the user,wherein the user sensory data is evaluated based on one or more usercharacteristics.
 10. The method of claim 9, wherein the one or more usercharacteristics comprise at least one of general human behavior,specific user behavior, user activities, user gaze points, user headlocations, and user distance from the display device.
 11. The method ofclaim 8, where the sensory input data comprises environment sensory datarelating to the surrounding environment, wherein the environment sensorydata is evaluated based on one or more ambient characteristics.
 12. Themethod of claim 11, wherein the one or more ambient characteristicscomprise at least one of ambient light brightness levels, ambient lightcolors, color space input settings, background views, temperaturesettings, power levels, display device intensity levels, display devicelimitations, and natural laws.
 13. The method of claim 8, wherein thesensory input data is collected using one or more capturing/sensingcomponents comprising at least one of a three-dimensional (3D) camera, adepth sensing camera, a camera sensor, a Red Green Blue (RGB) sensor, agaze tracking component, and a head tracking component.
 14. The methodof claim 8, wherein the display device comprises at least one of ahigh-resolution display, a high-dynamic range display, a multi-viewdisplay, and a head-mounted display (HMD) for at least one of virtualreality (VR) and augmented reality (AR).
 15. At least onemachine-readable medium comprising a plurality of instructions, executedon a computing device, to facilitate the computing device to perform oneor more operations comprising: collecting, in real time, sensory inputdata relating to characteristics of at least one of a user and asurrounding environment; evaluating the sensory input data to mark oneor more data portions of data relating to contents, wherein the one ormore data portions are determined to be suitable for compression basedon the sensory input data; dynamically performing, in real time, thecompression of the one or more data portions, wherein the compressiontriggers loss of one or more content portions of the contentscorresponding to the one or more data portions of the data; andrendering the contents to be displayed missing the one or more contentportions, wherein the missing of the one or more content portions fromthe contents is not apparent to the user viewing the contents via adisplay device.
 16. The machine-readable medium of claim 15, where thesensory input data comprises user sensory data relating to the user,wherein the user sensory data is evaluated based on one or more usercharacteristics.
 17. The machine-readable medium of claim 16, whereinthe one or more user characteristics comprise at least one of generalhuman behavior, specific user behavior, user activities, user gazepoints, user head locations, and user distance from the display device.18. The machine-readable medium of claim 15, where the sensory inputdata comprises environment sensory data relating to the surroundingenvironment, wherein the environment sensory data is evaluated based onone or more ambient characteristics.
 19. The machine-readable medium ofclaim 18, wherein the one or more ambient characteristics comprise atleast one of ambient light brightness levels, ambient light colors,color space input settings, background views, temperature settings,power levels, display device intensity levels, display devicelimitations, and natural laws.
 20. The machine-readable medium of claim15, wherein the sensory input data is collected using one or morecapturing/sensing components comprising at least one of athree-dimensional (3D) camera, a depth sensing camera, a camera sensor,a Red Green Blue (RGB) sensor, a gaze tracking component, and a headtracking component.
 21. The machine-readable medium of claim 15, whereinthe display device comprises at least one of a high-resolution display,a high-dynamic range display, a multi-view display, and a head-mounteddisplay (HMD) for at least one of virtual reality (VR) and augmentedreality (AR).